[B3] M.R.D. Rodrigues, S.C. Draper, W.U. Bajwa, and Y.C. Eldar, “Introduction to information theory and data science,” in Information-Theoretic Methods in Data Science, M.R.D. Rodrigues and Y.C. Eldar, Eds. Cambridge, UK: Cambridge University Press, 2021, Ch. 1, pp. 1-43. [BibTeX]

[B2] Z. Shakeri, A.D. Sarwate, and W.U. Bajwa, “Sample complexity bounds for dictionary learning from vector- and tensor-valued data,” in Information-Theoretic Methods in Data Science, M.R.D. Rodrigues and Y.C. Eldar, Eds. Cambridge, UK: Cambridge University Press, 2021, Ch. 5, pp. 134-162. [BibTeX]

[T6] T. Wu, P. Gurram, R.M. Rao, and W.U. Bajwa, “Human action attribute learning from video data using low-rank representations,” Technical Report 2020-07-001, Department of Electrical and Computer Engineering, Rutgers University, New Brunswick, NJ, Jul. 2020. [BibTeX]

[J] M.A. Lodhi and W.U. Bajwa, “Learning product graphs underlying smooth graph signals,” arXiv preprint, Jun. 2020. [BibTeX]

[J] R. Dixit and W.U. Bajwa, “Exit time analysis for approximations of gradient descent trajectories around saddle points,” arXiv preprint, Jun. 2020. [BibTeX]

[J] H. Raja and W.U. Bajwa, “Distributed stochastic algorithms for high-rate streaming principal component analysis,” arXiv preprint, Jan. 2020. [BibTeX]

[J] W.U. Bajwa and D. Mixon, “A multiple hypothesis testing approach to low-complexity subspace unmixing,” arXiv preprint. [BibTeX]

[J45] S. Liang, A. Higuera, C. Peters, V. Roy, W.U. Bajwa, H. Shatkay, and C.D. Tunnell, “Domain-informed neural networks for interaction localization within astroparticle experiments,” Front. Artif. Intell. – Big Data and AI in High Energy Physics, vol. 5, pp. 1–12, Jun. 2022. [BibTeX]

[J44] A. Nooraiepour, S. Vosoughitabar, C.-S.M. Wu, W.U. Bajwa, and N.B. Mandayam, “Time-varying metamaterial-enabled directional modulation schemes for physical layer security in wireless communication links,” ACM J. Emerg. Technol. Comput. Syst., 2022 (in press). [BibTeX]

[J43] A. Gang and W.U. Bajwa, “A linearly convergent algorithm for distributed principal component analysis,” EURASIP J. Signal Processing, vol. 193, pp. 108408, Apr. 2022. [BibTeX] [Elsevier ScienceDirect Version]

[J42] A. Nooraiepour, W.U. Bajwa, and N.B. Mandayam, “A hybrid model-based and learning-based approach for classification using limited number of training samples,” IEEE Open J. Signal Proc., vol. 3, pp. 49-70, Jan. 2022. [BibTeX] [IEEE Xplore Version]

[C94] B. Taki, M. Ghassemi, A.D. Sarwate, and W.U. Bajwa, “A minimax lower bound for low-rank matrix-variate logistic regression,” in Proc. 55th Asilomar Conf. Signals, Systems, and Computers, Pacific Grove, CA, Oct. 31-Nov. 3, 2021, pp. 477-484. [BibTeX] [IEEE Xplore Version]

[J41] P. Pandey, M. Rahmati, W.U. Bajwa, and D. Pompili, “Real-time in-network image compression via distributed dictionary learning,” IEEE Trans. Mobile Computing, 2021 (in press). [BibTeX] [IEEE Xplore Version]

[J40] A. Gang, B. Xiang, and W.U. Bajwa, “Distributed principal subspace analysis for partitioned big data: Algorithms, analysis, and implementation,” IEEE Trans. Signal Inform. Proc. over Netw., vol. 7, pp. 699-715, Oct. 2021. [BibTeX] [IEEE Xplore Version]

[C93] A. Nooraiepour, W.U. Bajwa, and N.B. Mandayam, “HyPhyLearn: A domain adaptation-inspired approach to classification using limited number of training samples,” in Proc. IEEE Intl. Workshop Machine Learning for Signal Processing (MLSP’21), Gold Coast, Australia, Oct. 25-28, 2021, pp. 1-6. [BibTeX] [IEEE Xplore Version]

[J39] A. Nooraiepour, W.U. Bajwa, and N.B. Mandayam, “Learning-aided physical layer attacks against multicarrier communications in IoT,” IEEE Trans. Cognitive Commun. Netw., vol. 7, no. 1, pp. 239-254, Mar. 2021. [BibTeX] [IEEE Xplore Version]

[J38] M. Nokleby, H. Raja, and W.U. Bajwa, “Scaling-up distributed processing of data streams for machine learning,” Proc. of the IEEE, vol. 108, no. 11, pp. 1984-2012, Nov. 2020. [BibTeX] [IEEE Xplore Version]

[J37] U.A. Khan, W.U. Bajwa, A. Nedić, M.G. Rabbat, and A.H. Sayed, “Optimization for data-driven learning and control,” Proc. of the IEEE, vol. 108, no. 11, pp. 1863-1868, Nov. 2020. [BibTeX] [IEEE Xplore Version]

[J36] T. Ahmed, H. Raja, and W.U. Bajwa, “Tensor regression using low-rank and sparse Tucker decompositions,” SIAM J. Math. Data Science, vol. 2, no. 4, pp. 944-966, 2020. [BibTeX] [SIAM Version]

[J35] Z. Yang, A. Gang, and W.U. Bajwa, “Adversary-resilient distributed and decentralized statistical inference and machine learning: An overview of recent advances under the Byzantine threat model,” IEEE Signal Processing Mag., vol. 37, no. 3, pp. 146-159, May 2020. Companion Code – DOI: 10.5281/zenodo.3952994. [BibTeX] [Code BibTeX] [IEEE Xplore Version]

[J34] W.U. Bajwa, V. Cevher, D. Papailiopoulos, and A. Scaglione, “Machine learning from distributed, streaming data,” IEEE Signal Processing Mag., vol. 37, no. 3, pp. 11-13, May 2020. [BibTeX] [IEEE Xplore Version]

[J33] M. Ghassemi, Z. Shakeri, A.D. Sarwate, and W.U. Bajwa, “Learning mixtures of separable dictionaries for tensor data: Analysis and algorithms,” IEEE Trans. Signal Processing, vol. 68, pp. 33-48, 2020. Companion Code – DOI: 10.5281/zenodo.3901852. [BibTeX] [Code BibTeX] [IEEE Xplore Version]

[J32] Z. Yang and W.U. Bajwa, “ByRDiE: Byzantine-resilient distributed coordinate descent for decentralized learning,” IEEE Trans. Signal Inform. Proc. over Netw., vol. 5, no. 4, pp. 611-627, Dec. 2019. Companion Code – DOI: 10.5281/zenodo.3952994. [BibTeX] [Code BibTeX] [IEEE Xplore Version]

[C92] Z. Yang and W.U. Bajwa, “PAC learning from distributed data in the presence of malicious nodes,” in Proc. 8th IEEE Intl. Workshop Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP’19), Guadeloupe, West Indies, Dec. 15-18, 2019, pp. 186-190. [BibTeX] [IEEE Xplore Version]

[J31] J.P. Dumas, M.A. Lodhi, B.A. Taki, W.U. Bajwa, and M.C. Pierce, “Computational endoscopy—A framework for improving spatial resolution in fiber bundle imaging,” Optics Letters, vol. 44, no. 16, pp. 3968-3971, 2019. [BibTeX]

[C91] M. Ghassemi, Z. Shakeri, A.D. Sarwate, and W.U. Bajwa, “Sample complexity bounds for low-separation-rank dictionary learning,” in Proc. IEEE Intl. Symp. Information Theory (ISIT’19), Paris, France, Jul. 7-12, 2019, pp. 2294-2298. [BibTeX] [IEEE Xplore Version]

[C90] Z. Shakeri, B.A. Taki, A.L.F. de Almeida, M. Ghassemi, and W.U. Bajwa, “Revisiting sparse channel estimation in massive MIMO-OFDM systems,” in Proc. IEEE Intl. Workshop on Signal Processing Advances in Wireless Communications (SPAWC’19), Cannes, France, Jul. 2-5, 2019, pp. 1-5. [BibTeX]

[J30] T. Ahmed and W.U. Bajwa, “ExSIS: Extended sure independence screening for ultrahigh-dimensional linear models,” EURASIP J. Signal Processing, vol. 159, pp. 33-48, Jun. 2019. [BibTeX] [Elsevier ScienceDirect Version]

[C89] A. Gang, H. Raja, and W.U. Bajwa, “Fast and communication-efficient distributed PCA,” in Proc. IEEE Intl. Conf. Acoustics, Speech, and Signal Processing (ICASSP’19), Brighton, UK, May 12-17, 2019, pp. 7450-7454. [BibTeX]

[J29] M. Nokleby and W.U. Bajwa, “Stochastic optimization from distributed, streaming data in rate-limited networks,” IEEE Trans. Signal Inform. Proc. over Netw., vol. 5, no. 1, pp. 152-167, Mar. 2019. [BibTeX] [IEEE Xplore Version]

[C88] J.P. Dumas, M.A. Lodhi, B.A. Taki, W.U. Bajwa, and M.C. Pierce, “A computational imaging approach for resolution enhancement in fiber bundle endomicroscopy,” in Proc. SPIE Conf. Endoscopic Microscopy XIV, San Francisco, CA, Feb. 2-4, 2019, pp. 1-7. [BibTeX] [SPIE Version]

[J] Z. Yang, A. Gang, and W.U. Bajwa, “Adversary-resilient distributed and decentralized statistical inference and machine learning: An overview of recent advances under the Byzantine threat model,” IEEE Signal Processing Mag., vol. 37, no. 3, pp. 146-159, May 2020. Companion Code – DOI: 10.5281/zenodo.3952994. [BibTeX] [Code BibTeX] [IEEE Xplore Version]

[J] Z. Yang and W.U. Bajwa, “ByRDiE: Byzantine-resilient distributed coordinate descent for decentralized learning,” IEEE Trans. Signal Inform. Proc. over Netw., vol. 5, no. 4, pp. 611-627, Dec. 2019. Companion Code – DOI: 10.5281/zenodo.3952994. [BibTeX] [Code BibTeX] [IEEE Xplore Version]

[C] Z. Yang and W.U. Bajwa, “PAC learning from distributed data in the presence of malicious nodes,” in Proc. 8th IEEE Intl. Workshop Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP’19), Guadeloupe, West Indies, Dec. 15-18, 2019, pp. 186-190. [BibTeX] [IEEE Xplore Version]

[C] Z. Yang and W.U. Bajwa, “ByRDiE: A Byzantine-resilient distributed learning algorithm,” in Proc. IEEE Data Science Workshop (DSW’18), Lausanne, Switzerland, Jun. 4-6, 2018, pp. 21-25. [BibTeX]

[C] Z. Yang and W.U. Bajwa, “RD-SVM: A resilient distributed support vector machine,” in Proc. IEEE Intl. Conf. Acoustics, Speech, and Signal Processing (ICASSP’16), Shanghai, China, Mar. 20-25, 2016, pp. 2444-2448. [BibTeX]

[J] A. Gang and W.U. Bajwa, “A linearly convergent algorithm for distributed principal component analysis,” EURASIP J. Signal Processing, vol. 193, pp. 108408, Apr. 2022. [BibTeX] [Elsevier ScienceDirect Version]

[J] A. Gang, B. Xiang, and W.U. Bajwa, “Distributed principal subspace analysis for partitioned big data: Algorithms, analysis, and implementation,” IEEE Trans. Signal Inform. Proc. over Netw., vol. 7, pp. 699-715, Oct. 2021. [BibTeX] [IEEE Xplore Version]

[J] R. Dixit and W.U. Bajwa, “Exit time analysis for approximations of gradient descent trajectories around saddle points,” arXiv preprint, Jun. 2020. [BibTeX]

[J] M. Nokleby, H. Raja, and W.U. Bajwa, “Scaling-up distributed processing of data streams for machine learning,” Proc. of the IEEE, vol. 108, no. 11, pp. 1984-2012, Nov. 2020. [BibTeX] [IEEE Xplore Version]

[J] U.A. Khan, W.U. Bajwa, A. Nedić, M.G. Rabbat, and A.H. Sayed, “Optimization for data-driven learning and control,” Proc. of the IEEE, vol. 108, no. 11, pp. 1863-1868, Nov. 2020. [BibTeX] [IEEE Xplore Version]

[J] H. Raja and W.U. Bajwa, “Distributed stochastic algorithms for high-rate streaming principal component analysis,” arXiv preprint, Jan. 2020. [BibTeX]

[J] Z. Yang, A. Gang, and W.U. Bajwa, “Adversary-resilient distributed and decentralized statistical inference and machine learning: An overview of recent advances under the Byzantine threat model,” IEEE Signal Processing Mag., vol. 37, no. 3, pp. 146-159, May 2020. Companion Code – DOI: 10.5281/zenodo.3952994. [BibTeX] [Code BibTeX] [IEEE Xplore Version]

[J] W.U. Bajwa, V. Cevher, D. Papailiopoulos, and A. Scaglione, “Machine learning from distributed, streaming data,” IEEE Signal Processing Mag., vol. 37, no. 3, pp. 11-13, May 2020. [BibTeX] [IEEE Xplore Version]

[J] Z. Yang and W.U. Bajwa, “ByRDiE: Byzantine-resilient distributed coordinate descent for decentralized learning,” IEEE Trans. Signal Inform. Proc. over Netw., vol. 5, no. 4, pp. 611-627, Dec. 2019. Companion Code – DOI: 10.5281/zenodo.3952994. [BibTeX] [Code BibTeX] [IEEE Xplore Version]

[C] Z. Yang and W.U. Bajwa, “PAC learning from distributed data in the presence of malicious nodes,” in Proc. 8th IEEE Intl. Workshop Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP’19), Guadeloupe, West Indies, Dec. 15-18, 2019, pp. 186-190. [BibTeX] [IEEE Xplore Version]

[C] A. Gang, H. Raja, and W.U. Bajwa, “Fast and communication-efficient distributed PCA,” in Proc. IEEE Intl. Conf. Acoustics, Speech, and Signal Processing (ICASSP’19), Brighton, UK, May 12-17, 2019, pp. 7450-7454. [BibTeX]

[J] M. Nokleby and W.U. Bajwa, “Stochastic optimization from distributed, streaming data in rate-limited networks,” IEEE Trans. Signal Inform. Proc. over Netw., vol. 5, no. 1, pp. 152-167, Mar. 2019. [BibTeX] [IEEE Xplore Version]

[C] Z. Yang and W.U. Bajwa, “ByRDiE: A Byzantine-resilient distributed learning algorithm,” in Proc. IEEE Data Science Workshop (DSW’18), Lausanne, Switzerland, Jun. 4-6, 2018, pp. 21-25. [BibTeX]

[C] M. Nokleby and W.U. Bajwa, “Distributed mirror descent for stochastic learning over rate-limited networks,” in Proc. 7th IEEE Intl. Workshop Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP’17), Curaçao, Dutch Antilles, Dec. 10-13, 2017, pp. 1-5. [BibTeX]

[C] H. Raja, W.U. Bajwa, and F. Ahmad, “Through-the-wall radar imaging using a distributed quasi-Newton method,” in Proc. 51st Asilomar Conf. Signals, Systems, and Computers, Pacific Grove, CA, Oct. 29-Nov. 1, 2017, pp. 85-89. [BibTeX]

[C] H. Raja, W.U. Bajwa, F. Ahmad, and M.G. Amin, “Parametric dictionary learning for TWRI using distributed particle swarm optimization,” in Proc. IEEE Radar Conf., Philadelphia, PA, May 2-6, 2016, pp. 1-5. [BibTeX]

[J] H. Raja and W.U. Bajwa, “Cloud K-SVD: A collaborative dictionary learning algorithm for big, distributed data,” IEEE Trans. Signal Processing, vol. 64, no. 1, pp. 173-188, Jan. 2016. Companion Code – Download from BitBucket. [BibTeX]

[C] H. Raja and W.U. Bajwa, “A convergence analysis of distributed dictionary learning based on the K-SVD algorithm,” in Proc. IEEE Intl. Symp. Information Theory (ISIT’15), Hong Kong, Jun. 14-19, 2015, pp. 2186-2190. [BibTeX]

[C] M. Nokleby and W.U. Bajwa, “Resource tradeoffs in distributed subspace tracking over the wireless medium,” in Proc. 1st IEEE Global Conf. Signal and Information Processing (GlobalSIP’13), Symposium on Network Theory, Austin, TX, Dec. 2013, pp. 823-826. [BibTeX]

[C] H. Raja and W.U. Bajwa, “Cloud K-SVD: Computing data-adaptive representations in the cloud,” in Proc. 51st Annu. Allerton Conf. Communication, Control, and Computing, Monticello, IL, Oct. 2-4, 2013, pp. pp. 1474-1481. [BibTeX]

[J] J.P. Dumas, M.A. Lodhi, B.A. Taki, W.U. Bajwa, and M.C. Pierce, “Computational endoscopy—A framework for improving spatial resolution in fiber bundle imaging,” Optics Letters, vol. 44, no. 16, pp. 3968-3971, 2019. [BibTeX]

[C] J.P. Dumas, M.A. Lodhi, B.A. Taki, W.U. Bajwa, and M.C. Pierce, “A computational imaging approach for resolution enhancement in fiber bundle endomicroscopy,” in Proc. SPIE Conf. Endoscopic Microscopy XIV, San Francisco, CA, Feb. 2-4, 2019, pp. 1-7. [BibTeX] [SPIE Version]

[C] J.P. Dumas, M.A. Lodhi, W.U. Bajwa, and M.C. Pierce, “A compressed sensing approach for resolution improvement in fiber-bundle based endomicroscopy,” in Proc. SPIE Conf. Endoscopic Microscopy XIII, San Francisco, CA, Jan. 27-29, 2018, pp. 1-7. [BibTeX]

[J] J.P. Dumas, M.A. Lodhi, W.U. Bajwa, and M.C. Pierce, “From modeling to hardware: An experimental evaluation of image plane and Fourier plane coded compressive optical imaging,” Optics Express, vol. 25, no. 23, pp. 29472-29491, Nov. 2017. [BibTeX]

[C] M.A. Lodhi, J.P. Dumas, M.C. Pierce, and W.U. Bajwa, “Computational imaging through a fiber-optic bundle,” in Proc. SPIE Conf. Compressive Sensing VI, Anaheim, CA, Apr. 12-13, 2017, pp. 1-11. [BibTeX]

[C] J.P. Dumas, M.A. Lodhi, W.U. Bajwa, and M.C. Pierce, “Evaluation of computational endomicroscopy architectures for minimally-invasive optical biopsy,” in Proc. SPIE Conf. Endoscopic Microscopy XII, San Francisco, CA, Jan. 29-30, 2017, pp. 1-7. [BibTeX]

[J] J.P. Dumas, M.A. Lodhi, W.U. Bajwa, and M.C. Pierce, “Computational imaging with a highly parallel image-plane-coded architecture: Challenges and solutions,” Optics Express, vol. 24, no. 6, pp. 6145-6155, Mar. 2016. [BibTeX]

[C] J.P. Dumas, M.C. Pierce, M.A. Lodhi, and W.U. Bajwa, “Design and characterization of a computational endomicroscopy platform for optical biopsy,” in Proc. Biomedical Optics 2016 (Clinical and Translational Biophotonics), Fort Lauderdale, FL, Apr. 25-28, 2016, p. JM3A.37. [BibTeX]

[J] A. Nooraiepour, W.U. Bajwa, and N.B. Mandayam, “A hybrid model-based and learning-based approach for classification using limited number of training samples,” IEEE Open J. Signal Proc., vol. 3, pp. 49-70, Jan. 2022. [BibTeX] [IEEE Xplore Version]

[C] B. Taki, M. Ghassemi, A.D. Sarwate, and W.U. Bajwa, “A minimax lower bound for low-rank matrix-variate logistic regression,” in Proc. 55th Asilomar Conf. Signals, Systems, and Computers, Pacific Grove, CA, Oct. 31-Nov. 3, 2021, pp. 477-484. [BibTeX] [IEEE Xplore Version]

[C] A. Nooraiepour, W.U. Bajwa, and N.B. Mandayam, “HyPhyLearn: A domain adaptation-inspired approach to classification using limited number of training samples,” in Proc. IEEE Intl. Workshop Machine Learning for Signal Processing (MLSP’21), Gold Coast, Australia, Oct. 25-28, 2021, pp. 1-6. [BibTeX] [IEEE Xplore Version]

[C] A. Burns and W.U. Bajwa, “Multispectral imaging for improved liquid classification in security sensor systems,” in Proc. SPIE Conf. Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXIV, Orlando, FL, Apr. 17-19, 2018, pp. 1-7. [BibTeX]

[J] S. Parlak, I. Marsic, A. Sarcevic, W.U. Bajwa, L. Waterhouse, and R. Burd, “Passive RFID for object and use detection during trauma resuscitation,” IEEE Trans. Mobile Computing, vol. 15, no. 4, pp. 924-937, Apr. 2016. [BibTeX]

[J] A. Gang and W.U. Bajwa, “A linearly convergent algorithm for distributed principal component analysis,” EURASIP J. Signal Processing, vol. 193, pp. 108408, Apr. 2022. [BibTeX] [Elsevier ScienceDirect Version]

[J] A. Gang, B. Xiang, and W.U. Bajwa, “Distributed principal subspace analysis for partitioned big data: Algorithms, analysis, and implementation,” IEEE Trans. Signal Inform. Proc. over Netw., vol. 7, pp. 699-715, Oct. 2021. [BibTeX] [IEEE Xplore Version]

[J] P. Pandey, M. Rahmati, W.U. Bajwa, and D. Pompili, “Real-time in-network image compression via distributed dictionary learning,” IEEE Trans. Mobile Computing, 2021 (in press). [BibTeX] [IEEE Xplore Version]

[B] Z. Shakeri, A.D. Sarwate, and W.U. Bajwa, “Sample complexity bounds for dictionary learning from vector- and tensor-valued data,” in Information-Theoretic Methods in Data Science, M.R.D. Rodrigues and Y.C. Eldar, Eds. Cambridge, UK: Cambridge University Press, 2021, Ch. 5, pp. 134-162. [BibTeX]

[J] M. Nokleby, H. Raja, and W.U. Bajwa, “Scaling-up distributed processing of data streams for machine learning,” Proc. of the IEEE, vol. 108, no. 11, pp. 1984-2012, Nov. 2020. [BibTeX] [IEEE Xplore Version]

[T] T. Wu, P. Gurram, R.M. Rao, and W.U. Bajwa, “Human action attribute learning from video data using low-rank representations,” Technical Report 2020-07-001, Department of Electrical and Computer Engineering, Rutgers University, New Brunswick, NJ, Jul. 2020. [BibTeX]

[J] H. Raja and W.U. Bajwa, “Distributed stochastic algorithms for high-rate streaming principal component analysis,” arXiv preprint, Jan. 2020. [BibTeX]

[J] M. Ghassemi, Z. Shakeri, A.D. Sarwate, and W.U. Bajwa, “Learning mixtures of separable dictionaries for tensor data: Analysis and algorithms,” IEEE Trans. Signal Processing, vol. 68, pp. 33-48, 2020. Companion Code – DOI: 10.5281/zenodo.3901852. [BibTeX] [Code BibTeX] [IEEE Xplore Version]

[C] M. Ghassemi, Z. Shakeri, A.D. Sarwate, and W.U. Bajwa, “Sample complexity bounds for low-separation-rank dictionary learning,” in Proc. IEEE Intl. Symp. Information Theory (ISIT’19), Paris, France, Jul. 7-12, 2019, pp. 2294-2298. [BibTeX] [IEEE Xplore Version]

[C] A. Gang, H. Raja, and W.U. Bajwa, “Fast and communication-efficient distributed PCA,” in Proc. IEEE Intl. Conf. Acoustics, Speech, and Signal Processing (ICASSP’19), Brighton, UK, May 12-17, 2019, pp. 7450-7454. [BibTeX]

[J] Z. Shakeri, A.D. Sarwate, and W.U. Bajwa, “Identifiability of Kronecker-structured dictionaries for tensor data,” IEEE J. Sel. Topics Signal Processing, , vol. 12, no. 5, pp. 1047-1062, Oct. 2018. [BibTeX]

[C] P. Pandey, M. Rahmati, D. Pompili, and W.U. Bajwa, “Robust distributed dictionary learning for in-network image compression,” in Proc. IEEE Intl. Conf. Autonomic Computing (ICAC’18), Trento, Italy, Sep. 3-7, 2018, pp. 61-70. [BibTeX]

[J] T. Wu and W.U. Bajwa, “A low tensor-rank representation approach for clustering of imaging data,” IEEE Signal Processing Letters, vol. 25, no. 8, pp. 1196-1200, Aug. 2018. [BibTeX]

[J] Z. Shakeri, W.U. Bajwa, and A.D. Sarwate, “Minimax lower bounds on dictionary learning for tensor data,” IEEE Trans. Inform. Theory, vol. 64, no. 4, pp. 2706-2726, Apr. 2018. [BibTeX]

[C] Z. Shakeri, A.D. Sarwate, and W.U. Bajwa, “Identification of Kronecker-structured dictionaries: An asymptotic analysis,” in Proc. 7th IEEE Intl. Workshop Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP’17), Curaçao, Dutch Antilles, Dec. 10-13, 2017, pp. 1-5. [BibTeX]

[C] M. Ghassemi, Z. Shakeri, A.D. Sarwate, and W.U. Bajwa, “STARK: Structured dictionary learning through rank-one tensor recovery,” in Proc. 7th IEEE Intl. Workshop Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP’17), Curaçao, Dutch Antilles, Dec. 10-13, 2017, pp. 1-5. [BibTeX]

[C] H. Raja, W.U. Bajwa, and F. Ahmad, “Through-the-wall radar imaging using a distributed quasi-Newton method,” in Proc. 51st Asilomar Conf. Signals, Systems, and Computers, Pacific Grove, CA, Oct. 29-Nov. 1, 2017, pp. 85-89. [BibTeX]

[C] T. Wu, P. Gurram, R.M. Rao, and W.U. Bajwa, “Human action attribute learning using low-rank representations,” in Proc. Workshop Signal Processing with Adaptive Sparse Structured Representations (SPARS’17), Lisbon, Portugal, Jun. 5-8, 2017. [BibTeX]

[C] Z. Shakeri, W.U. Bajwa, and A.D. Sarwate, “Minimax lower bounds for dictionary learning from tensor data,” in Proc. Workshop Signal Processing with Adaptive Sparse Structured Representations (SPARS’17), Lisbon, Portugal, Jun. 5-8, 2017. [BibTeX]

[C] Z. Shakeri, W.U. Bajwa, and A.D. Sarwate, “Sample complexity bounds for dictionary learning of tensor data,” in Proc. IEEE Intl. Conf. Acoustics, Speech, and Signal Processing (ICASSP’17), New Orleans, LA, Mar. 5-9, 2017, pp. 4501-4505. [BibTeX]

[C] Z. Shakeri, W.U. Bajwa, and A.D. Sarwate, “Minimax lower bounds for Kronecker-structured dictionary learning,” in Proc. IEEE Intl. Symp. Information Theory (ISIT’16), Barcelona, Spain, Jul. 10-15, 2016, pp. 1148-1152. [BibTeX]

[C] Z. Shakeri and W.U. Bajwa, “Revisiting maximal response-based local identification of overcomplete dictionaries,” in Proc. IEEE Intl. Workshop on Sensor Array and Multichannel Signal Processing (SAM’16), Rio de Janeiro, Brazil, Jul. 10-13, 2016, pp. 1-5. [BibTeX]

[C] T. Wu, P. Gurram, R.M. Rao, and W.U. Bajwa, “Clustering-aware structure-constrained low-rank representation model for learning human action attributes,” in Proc. IEEE Intl. Workshop on Image, Video and Multidimensional Signal Processing (IVMSP’16), Bordeaux, France, Jul. 11-12, 2016, pp. 1-5. [BibTeX] (Winner of the Best Student Paper Award)

[C] H. Raja, W.U. Bajwa, F. Ahmad, and M.G. Amin, “Parametric dictionary learning for TWRI using distributed particle swarm optimization,” in Proc. IEEE Radar Conf., Philadelphia, PA, May 2-6, 2016, pp. 1-5. [BibTeX]

[C] H. Raja and W.U. Bajwa, “Learning overcomplete representations from distributed data: A brief review,” in Proc. SPIE Defense and Commercial Sensing Conf. Compressive Sensing, Baltimore, MD, Apr. 17-21, 2016, pp. 1-14. [BibTeX]

[J] H. Raja and W.U. Bajwa, “Cloud K-SVD: A collaborative dictionary learning algorithm for big, distributed data,” IEEE Trans. Signal Processing, vol. 64, no. 1, pp. 173-188, Jan. 2016. Companion Code – Download from BitBucket. [BibTeX]

[J] T. Wu and W.U. Bajwa, “Learning the nonlinear geometry of high-dimensional data: Models and algorithms,” IEEE Trans. Signal Processing, vol. 63, no. 23, pp. 6229-6244, Dec. 2015. Companion Code – Download from BitBucket. [BibTeX]

[C] T. Wu, P. Gurram, R.M. Rao, and W.U. Bajwa, “Hierarchical union-of-subspaces model for human activity summarization,” in Proc. IEEE Intl. Conf. Computer Vision, Workshop on Video Summarization for Large-Scale Analytics, Santiago, Chile, Dec. 11-18, 2015, pp. 1053-1061. [BibTeX]

[C] H. Raja and W.U. Bajwa, “A convergence analysis of distributed dictionary learning based on the K-SVD algorithm,” in Proc. IEEE Intl. Symp. Information Theory (ISIT’15), Hong Kong, Jun. 14-19, 2015, pp. 2186-2190. [BibTeX]

[C] T. Wu and W.U. Bajwa, “Metric-constrained kernel union of subspaces,” in Proc. IEEE Intl. Conf. Acoustics, Speech, and Signal Processing (ICASSP’15), Brisbane, Australia, Apr. 19-24, 2015, pp. 5778-5782. [BibTeX]

[C] T. Wu, A. Sarwate, and W.U. Bajwa, “Active dictionary learning for image representation,” in Proc. SPIE Unmanned Systems Technology XVII, Baltimore, MD, Apr. 21-23, 2015, pp. 1-10. [BibTeX]

[C] Z. Shakeri, H. Raja, and W.U. Bajwa, “Dictionary learning based nonlinear classifier training from distributed data,” in Proc. 2nd IEEE Global Conf. Signal and Information Processing (GlobalSIP’14), Symposium on Network Theory, Atlanta, GA, Dec. 3-5, 2014, pp. 759-763. [BibTeX]

[C] T. Ahmed and W.U. Bajwa, “Geometric manifold approximation using union of tangent patches,” in Proc. 2nd IEEE Global Conf. Signal and Information Processing (GlobalSIP’14), Symposium on Information Processing for Big Data, Atlanta, GA, Dec. 3-5, 2014, pp. 458-462. [BibTeX]

[C] T. Ahmed and W.U. Bajwa, “A greedy, adaptive approach to learning geometry of nonlinear manifolds,” in Proc. IEEE Workshop Statistical Signal Processing (SSP’14), Gold Coast, Australia, Jun. 29-Jul. 2, 2014, pp. 133-136. [BibTeX]

[C] T. Wu and W.U. Bajwa, “Revisiting robustness of the union-of-subspaces model for data-adaptive learning of nonlinear signal models,” in Proc. IEEE Intl. Conf. Acoustics, Speech, and Signal Processing (ICASSP’14), Florence, Italy, May 4-9, 2014, pp. 3390-3394. [BibTeX]

[C] M. Nokleby and W.U. Bajwa, “Resource tradeoffs in distributed subspace tracking over the wireless medium,” in Proc. 1st IEEE Global Conf. Signal and Information Processing (GlobalSIP’13), Symposium on Network Theory, Austin, TX, Dec. 2013, pp. 823-826. [BibTeX]

[C] H. Raja and W.U. Bajwa, “Cloud K-SVD: Computing data-adaptive representations in the cloud,” in Proc. 51st Annu. Allerton Conf. Communication, Control, and Computing, Monticello, IL, Oct. 2-4, 2013, pp. pp. 1474-1481. [BibTeX]

[C] L. Balzano, R. Nowak, and W.U. Bajwa, “Column subset selection with missing data,” in Proc. NIPS Workshop on Low-rank Methods for Large-scale Machine Learning, Whistler, Canada, Dec. 11, 2010. [BibTeX]

[J] A. Gang and W.U. Bajwa, “A linearly convergent algorithm for distributed principal component analysis,” EURASIP J. Signal Processing, vol. 193, pp. 108408, Apr. 2022. [BibTeX] [Elsevier ScienceDirect Version]

[J] A. Gang, B. Xiang, and W.U. Bajwa, “Distributed principal subspace analysis for partitioned big data: Algorithms, analysis, and implementation,” IEEE Trans. Signal Inform. Proc. over Netw., vol. 7, pp. 699-715, Oct. 2021. [BibTeX] [IEEE Xplore Version]

[J] P. Pandey, M. Rahmati, W.U. Bajwa, and D. Pompili, “Real-time in-network image compression via distributed dictionary learning,” IEEE Trans. Mobile Computing, 2021 (in press). [BibTeX] [IEEE Xplore Version]

[J] M. Nokleby, H. Raja, and W.U. Bajwa, “Scaling-up distributed processing of data streams for machine learning,” Proc. of the IEEE, vol. 108, no. 11, pp. 1984-2012, Nov. 2020. [BibTeX] [IEEE Xplore Version]

[J] U.A. Khan, W.U. Bajwa, A. Nedić, M.G. Rabbat, and A.H. Sayed, “Optimization for data-driven learning and control,” Proc. of the IEEE, vol. 108, no. 11, pp. 1863-1868, Nov. 2020. [BibTeX] [IEEE Xplore Version]

[J] H. Raja and W.U. Bajwa, “Distributed stochastic algorithms for high-rate streaming principal component analysis,” arXiv preprint, Jan. 2020. [BibTeX]

[J] Z. Yang, A. Gang, and W.U. Bajwa, “Adversary-resilient distributed and decentralized statistical inference and machine learning: An overview of recent advances under the Byzantine threat model,” IEEE Signal Processing Mag., vol. 37, no. 3, pp. 146-159, May 2020. Companion Code – DOI: 10.5281/zenodo.3952994. [BibTeX] [Code BibTeX] [IEEE Xplore Version]

[J] W.U. Bajwa, V. Cevher, D. Papailiopoulos, and A. Scaglione, “Machine learning from distributed, streaming data,” IEEE Signal Processing Mag., vol. 37, no. 3, pp. 11-13, May 2020. [BibTeX] [IEEE Xplore Version]

[J] Z. Yang and W.U. Bajwa, “ByRDiE: Byzantine-resilient distributed coordinate descent for decentralized learning,” IEEE Trans. Signal Inform. Proc. over Netw., vol. 5, no. 4, pp. 611-627, Dec. 2019. Companion Code – DOI: 10.5281/zenodo.3952994. [BibTeX] [Code BibTeX] [IEEE Xplore Version]

[C] Z. Yang and W.U. Bajwa, “PAC learning from distributed data in the presence of malicious nodes,” in Proc. 8th IEEE Intl. Workshop Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP’19), Guadeloupe, West Indies, Dec. 15-18, 2019, pp. 186-190. [BibTeX] [IEEE Xplore Version]

[C] A. Gang, H. Raja, and W.U. Bajwa, “Fast and communication-efficient distributed PCA,” in Proc. IEEE Intl. Conf. Acoustics, Speech, and Signal Processing (ICASSP’19), Brighton, UK, May 12-17, 2019, pp. 7450-7454. [BibTeX]

[J] M. Nokleby and W.U. Bajwa, “Stochastic optimization from distributed, streaming data in rate-limited networks,” IEEE Trans. Signal Inform. Proc. over Netw., vol. 5, no. 1, pp. 152-167, Mar. 2019. [BibTeX] [IEEE Xplore Version]

[C] P. Pandey, M. Rahmati, D. Pompili, and W.U. Bajwa, “Robust distributed dictionary learning for in-network image compression,” in Proc. IEEE Intl. Conf. Autonomic Computing (ICAC’18), Trento, Italy, Sep. 3-7, 2018, pp. 61-70. [BibTeX]

[C] Z. Yang and W.U. Bajwa, “ByRDiE: A Byzantine-resilient distributed learning algorithm,” in Proc. IEEE Data Science Workshop (DSW’18), Lausanne, Switzerland, Jun. 4-6, 2018, pp. 21-25. [BibTeX]

[C] M. Nokleby and W.U. Bajwa, “Distributed mirror descent for stochastic learning over rate-limited networks,” in Proc. 7th IEEE Intl. Workshop Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP’17), Curaçao, Dutch Antilles, Dec. 10-13, 2017, pp. 1-5. [BibTeX]

[C] H. Raja, W.U. Bajwa, and F. Ahmad, “Through-the-wall radar imaging using a distributed quasi-Newton method,” in Proc. 51st Asilomar Conf. Signals, Systems, and Computers, Pacific Grove, CA, Oct. 29-Nov. 1, 2017, pp. 85-89. [BibTeX]

[C] R. Pilgrim, J. Zhu, D. Baron, and W.U. Bajwa, “Generalized geometric programming for rate allocation in consensus,” in Proc. 55th Annu. Allerton Conf. Communication, Control, and Computing, Monticello, IL, Oct. 4-6, 2017, pp. 374-381. [BibTeX]

[C] H. Raja, W.U. Bajwa, F. Ahmad, and M.G. Amin, “Parametric dictionary learning for TWRI using distributed particle swarm optimization,” in Proc. IEEE Radar Conf., Philadelphia, PA, May 2-6, 2016, pp. 1-5. [BibTeX]

[C] H. Raja and W.U. Bajwa, “Learning overcomplete representations from distributed data: A brief review,” in Proc. SPIE Defense and Commercial Sensing Conf. Compressive Sensing, Baltimore, MD, Apr. 17-21, 2016, pp. 1-14. [BibTeX]

[C] Z. Yang and W.U. Bajwa, “RD-SVM: A resilient distributed support vector machine,” in Proc. IEEE Intl. Conf. Acoustics, Speech, and Signal Processing (ICASSP’16), Shanghai, China, Mar. 20-25, 2016, pp. 2444-2448. [BibTeX]

[J] H. Raja and W.U. Bajwa, “Cloud K-SVD: A collaborative dictionary learning algorithm for big, distributed data,” IEEE Trans. Signal Processing, vol. 64, no. 1, pp. 173-188, Jan. 2016. Companion Code – Download from BitBucket. [BibTeX]

[C] H. Raja and W.U. Bajwa, “A convergence analysis of distributed dictionary learning based on the K-SVD algorithm,” in Proc. IEEE Intl. Symp. Information Theory (ISIT’15), Hong Kong, Jun. 14-19, 2015, pp. 2186-2190. [BibTeX]

[C] Z. Shakeri, H. Raja, and W.U. Bajwa, “Dictionary learning based nonlinear classifier training from distributed data,” in Proc. 2nd IEEE Global Conf. Signal and Information Processing (GlobalSIP’14), Symposium on Network Theory, Atlanta, GA, Dec. 3-5, 2014, pp. 759-763. [BibTeX]

[C] M. Nokleby and W.U. Bajwa, “Resource tradeoffs in distributed subspace tracking over the wireless medium,” in Proc. 1st IEEE Global Conf. Signal and Information Processing (GlobalSIP’13), Symposium on Network Theory, Austin, TX, Dec. 2013, pp. 823-826. [BibTeX]

[C] H. Raja and W.U. Bajwa, “Cloud K-SVD: Computing data-adaptive representations in the cloud,” in Proc. 51st Annu. Allerton Conf. Communication, Control, and Computing, Monticello, IL, Oct. 2-4, 2013, pp. pp. 1474-1481. [BibTeX]

[J] M. Nokleby, W.U. Bajwa, R. Calderbank, and B. Aazhang, “Toward resource-optimal consensus over the wireless medium,” IEEE J. Select. Topics Signal Processing, vol. 7, no. 2, pp. 284-295, Apr. 2013. [BibTeX]

[C] M. Nokleby, W.U. Bajwa, R. Calderbank, and B. Aazhang, “Toward resource-optimal averaging consensus over the wireless medium,” in Proc. 46th Asilomar Conf. Signals, Systems, and Computers, Pacific Grove, CA, Nov. 4-7, 2012, pp. 1197-1201. [BibTeX]

[C] M. Nokleby, W.U. Bajwa, R. Calderbank, and B. Aazhang, “Hierarchical averaging over wireless networks,” in Proc. IEEE Intl. Conf. Acoustics, Speech, and Signal Processing (ICASSP’12), Kyoto, Japan, Mar. 25-30, 2012, pp. 3121-3124. [Erratum] [BibTeX]

[C] M. Nokleby, W.U. Bajwa, R. Calderbank, and B. Aazhang, “Gossiping in groups: Distributed averaging over the wireless medium,” in Proc. 49th Annu. Allerton Conf. Communication, Control, and Computing, Monticello, IL, Sep. 28-30, 2011, pp. 1242-1249. [BibTeX]

[J] J. Haupt, W.U. Bajwa, M. Rabbat, and R. Nowak, “Compressed sensing and network monitoring,” The Next Wave, vol. 18, no. 3, pp. 16-25, 2010. [BibTeX]

[J] J. Haupt, W.U. Bajwa, M. Rabbat, and R. Nowak, “Compressed sensing for networked data,” IEEE Signal Processing Mag., vol. 25, no. 2, pp. 92-101, Mar. 2008. [BibTeX]

[J] W.U. Bajwa, J. Haupt, A.M. Sayeed, and R. Nowak, “Joint source–channel communication for distributed estimation in sensor networks,” IEEE Trans. Inform. Theory, vol. 53, no. 10, pp. 3629-3653, Oct. 2007. [BibTeX]

[C] W.U. Bajwa, J. Haupt, A.M. Sayeed, and R. Nowak, “A universal matched source-channel communication scheme for wireless sensor ensembles,” in Proc. IEEE Intl. Conf. Acoustics, Speech, and Signal Processing (ICASSP’06), Toulouse, France, May 14-19, 2006, vol. 5, pp. 1153-1156. [BibTeX]

[C] W.U. Bajwa, J. Haupt, A.M. Sayeed, and R. Nowak, “Compressive wireless sensing,” in Proc. 5th ACM/IEEE Intl. Conf. Information Processing in Sensor Networks (IPSN’06), Nashville, TN, Apr. 19-21, 2006, pp. 134-142 (Acceptance rate: 41/165). [BibTeX]

[C] W.U. Bajwa, A.M. Sayeed, and R. Nowak, “Matched source-channel communication for field estimation in wireless sensor networks,” in Proc. 4th ACM/IEEE Intl. Conf. Information Processing in Sensor Networks (IPSN’05), Los Angeles, CA, Apr. 25-27, 2005, pp. 332-339 (Acceptance rate: 44/213). [BibTeX]

[C] W.U. Bajwa, A.M. Sayeed, and R. Nowak, “Efficient communication strategies for distributed signal field estimation,” in Proc. 38th Asilomar Conf. Signals, Systems, and Computers, Pacific Grove, CA, Nov. 7-10, 2004, pp. 1371-1375. [BibTeX]

[J] S. Liang, A. Higuera, C. Peters, V. Roy, W.U. Bajwa, H. Shatkay, and C.D. Tunnell, “Domain-informed neural networks for interaction localization within astroparticle experiments,” Front. Artif. Intell. – Big Data and AI in High Energy Physics, vol. 5, pp. 1–12, Jun. 2022. [BibTeX]

[J] M.A. Lodhi and W.U. Bajwa, “Learning product graphs underlying smooth graph signals,” arXiv preprint, Jun. 2020. [BibTeX]

[C] B. Taki, M. Ghassemi, A.D. Sarwate, and W.U. Bajwa, “A minimax lower bound for low-rank matrix-variate logistic regression,” in Proc. 55th Asilomar Conf. Signals, Systems, and Computers, Pacific Grove, CA, Oct. 31-Nov. 3, 2021, pp. 477-484. [BibTeX] [IEEE Xplore Version]

[J] T. Ahmed, H. Raja, and W.U. Bajwa, “Tensor regression using low-rank and sparse Tucker decompositions,” SIAM J. Math. Data Science, vol. 2, no. 4, pp. 944-966, 2020. [BibTeX] [SIAM Version]

[J] W.U. Bajwa and D. Mixon, “A multiple hypothesis testing approach to low-complexity subspace unmixing,” arXiv preprint. [BibTeX]

[J] T. Ahmed and W.U. Bajwa, “ExSIS: Extended sure independence screening for ultrahigh-dimensional linear models,” EURASIP J. Signal Processing, vol. 159, pp. 33-48, Jun. 2019. [BibTeX] [Elsevier ScienceDirect Version]

[J] M.A. Lodhi and W.U. Bajwa, “Detection theory for union of subspaces,” IEEE Trans. Signal Processing, vol. 66, no. 24, pp. 6347-6362, Dec. 2018. [BibTeX]

[C] M.A. Lodhi and W.U. Bajwa, “Union of subspaces signal detection in subspace interference,” in Proc. IEEE Workshop Statistical Signal Processing (SSP’18), Freiburg, Germany, Jun. 10-13, 2018, pp. 548-552. [BibTeX]

[C] T. Ahmed and W.U. Bajwa, “Correlation-based ultrahigh-dimensional variable screening,” in Proc. 7th IEEE Intl. Workshop Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP’17), Curaçao, Dutch Antilles, Dec. 10-13, 2017, pp. 1-5. [BibTeX] (Winner of Best Student Paper Award)

[J] W.U. Bajwa, M.F. Duarte, and R. Calderbank, “Conditioning of random block subdictionaries with applications to block-sparse recovery and regression,” IEEE Trans. Information Theory, vol. 61, no. 7, pp. 4060-4079, Jul. 2015. Companion Code – Download from BitBucket. [BibTeX]

[C] T. Wu and W.U. Bajwa, “Subspace detection in a kernel space: The missing data case,” in Proc. IEEE Workshop Statistical Signal Processing (SSP’14), Gold Coast, Australia, Jun. 29-Jul. 2, 2014, pp. 93-96. [BibTeX]

[C] W.U. Bajwa, M.F. Duarte, and R. Calderbank, “Average case analysis of high-dimensional block-sparse recovery and regression for arbitrary designs,” in Proc. 17th Intl. Conf. Artificial Intelligence and Statistics (AISTATS’14), Reykjavik, Iceland, Apr. 22-25, 2014, pp. 57-67 (Acceptance rate: 120/335). [BibTeX]

[J] A. Armagan, D.B. Dunson, J. Lee, W.U. Bajwa, and N. Strawn, “Posterior consistency in linear models under shrinkage priors,” Biometrika, vol. 100, no. 4, pp. 1011-1018, Dec. 2013. [BibTeX]

[J] K. Krishnamurthy, W.U. Bajwa, and R. Willett, “Level set estimation from projection measurements: Performance guarantees and fast computation,” SIAM J. Imaging Sciences, vol. 6, no. 4, pp. 2047-2074, Oct. 2013. [BibTeX]

[C] W.U. Bajwa and D.G. Mixon, “Group model selection using marginal correlations: The good, the bad and the ugly,” in Proc. 50th Annu. Allerton Conf. Communication, Control, and Computing, Monticello, IL, Oct. 1-5, 2012, pp. 494-501. [BibTeX]

[J] W.U. Bajwa, R. Calderbank, and D.G. Mixon, “Two are better than one: Fundamental parameters of frame coherence,” Appl. Comput. Harmon. Anal., vol. 33, no. 1, pp. 58-78, Jul. 2012. [BibTeX]

[C] K. Krishnamurthy, W.U. Bajwa, R. Willett, and R. Calderbank, “Fast level set estimation from projection measurements,” in Proc. IEEE Workshop Statistical Signal Processing (SSP’11), Nice, France, Jun. 28-30, 2011, pp. 585-588. [BibTeX]

[C] M.F. Duarte, W.U. Bajwa, and R. Calderbank, “Regression performance of group lasso for arbitrary design matrices,” in Proc. Intl. Conf. Sampling Theory and Applications (SampTA’11), Singapore, May 2-6, 2011. [BibTeX]

[C] W.U. Bajwa, R. Calderbank, and S. Jafarpour, “Revisiting model selection and recovery of sparse signals using one-step thresholding,” in Proc. 48th Annu. Allerton Conf. Communication, Control, and Computing, Monticello, IL, Sep. 29-Oct. 01, 2010, pp. 977-984. [BibTeX]

[J] W.U. Bajwa, R. Calderbank, and S. Jafarpour, “Why Gabor frames? Two fundamental measures of coherence and their role in model selection,” J. Commun. Netw., vol. 12, no. 4, pp. 289-307, Aug. 2010. [BibTeX]

[C] W.U. Bajwa, R. Calderbank, and S. Jafarpour, “Model selection: Two fundamental measures of coherence and their algorithmic significance,” in Proc. IEEE Intl. Symp. Information Theory (ISIT’10), Austin, TX, Jun. 13-18, 2010, pp. 1568-1572. [BibTeX]

[B] M.R.D. Rodrigues, S.C. Draper, W.U. Bajwa, and Y.C. Eldar, “Introduction to information theory and data science,” in Information-Theoretic Methods in Data Science, M.R.D. Rodrigues and Y.C. Eldar, Eds. Cambridge, UK: Cambridge University Press, 2021, Ch. 1, pp. 1-43. [BibTeX]

[B] Z. Shakeri, A.D. Sarwate, and W.U. Bajwa, “Sample complexity bounds for dictionary learning from vector- and tensor-valued data,” in Information-Theoretic Methods in Data Science, M.R.D. Rodrigues and Y.C. Eldar, Eds. Cambridge, UK: Cambridge University Press, 2021, Ch. 5, pp. 134-162. [BibTeX]

[J] M. Nokleby, H. Raja, and W.U. Bajwa, “Scaling-up distributed processing of data streams for machine learning,” Proc. of the IEEE, vol. 108, no. 11, pp. 1984-2012, Nov. 2020. [BibTeX] [IEEE Xplore Version]

[J] U.A. Khan, W.U. Bajwa, A. Nedić, M.G. Rabbat, and A.H. Sayed, “Optimization for data-driven learning and control,” Proc. of the IEEE, vol. 108, no. 11, pp. 1863-1868, Nov. 2020. [BibTeX] [IEEE Xplore Version]

[J] Z. Yang, A. Gang, and W.U. Bajwa, “Adversary-resilient distributed and decentralized statistical inference and machine learning: An overview of recent advances under the Byzantine threat model,” IEEE Signal Processing Mag., vol. 37, no. 3, pp. 146-159, May 2020. Companion Code – DOI: 10.5281/zenodo.3952994. [BibTeX] [Code BibTeX] [IEEE Xplore Version]

[C] H. Raja and W.U. Bajwa, “Learning overcomplete representations from distributed data: A brief review,” in Proc. SPIE Defense and Commercial Sensing Conf. Compressive Sensing, Baltimore, MD, Apr. 17-21, 2016, pp. 1-14. [BibTeX]

[B] W.U. Bajwa and A. Pezeshki, “Finite frames for sparse signal processing,” in Finite Frames, P. Casazza and G. Kutyniok, Eds. Cambridge, MA: Birkhäuser Boston, 2012, Ch. 10, pp. 303-335. [BibTeX]

[J] W.U. Bajwa, J. Haupt, A.M. Sayeed, and R. Nowak, “Compressed channel sensing: A new approach to estimating sparse multipath channels,” Proc. of the IEEE, vol. 98, no. 6, pp. 1058-1076, Jun. 2010. [BibTeX]

[J] J. Haupt, W.U. Bajwa, M. Rabbat, and R. Nowak, “Compressed sensing and network monitoring,” The Next Wave, vol. 18, no. 3, pp. 16-25, 2010. [BibTeX]

[T] W.U. Bajwa, “New information processing theory and methods for exploiting sparsity in wireless systems,” Ph.D. Dissertation, University of Wisconsin-Madison, Madison, WI, 2009. [BibTeX]

[J] J. Haupt, W.U. Bajwa, M. Rabbat, and R. Nowak, “Compressed sensing for networked data,” IEEE Signal Processing Mag., vol. 25, no. 2, pp. 92-101, Mar. 2008. [BibTeX]

[C] W.U. Bajwa, “Flipping large classes on a shoestring budget,” in Proc. IEEE Intl. Conf. Acoustics, Speech, and Signal Processing (ICASSP’18), Calgary, Canada, Apr. 15-20, 2018, pp. 7006-7010. [BibTeX]

[J] W.U. Bajwa, “On flipping a large signal processing class,” IEEE Signal Processing Mag., vol. 34, no. 4, pp. 158-170, Jul. 2017. [BibTeX]

[C] H. Raja, W.U. Bajwa, and F. Ahmad, “Through-the-wall radar imaging using a distributed quasi-Newton method,” in Proc. 51st Asilomar Conf. Signals, Systems, and Computers, Pacific Grove, CA, Oct. 29-Nov. 1, 2017, pp. 85-89. [BibTeX]

[C] H. Raja, W.U. Bajwa, F. Ahmad, and M.G. Amin, “Parametric dictionary learning for TWRI using distributed particle swarm optimization,” in Proc. IEEE Radar Conf., Philadelphia, PA, May 2-6, 2016, pp. 1-5. [BibTeX]

[J] S. Sun, W.U. Bajwa, and A.P. Petropulu, “MIMO-MC radar: A MIMO radar approach based on matrix completion,” IEEE Trans. Aerosp. Electron. Syst., vol. 51, no. 3, pp. 1839-1852, Jul. 2015. [BibTeX]

[J] A. Harms, W.U. Bajwa, and R. Calderbank, “Identification of linear time-varying systems through waveform diversity,” IEEE Trans. Signal Processing, vol. 63, no. 8, pp. 2070-2084, Apr. 2015. [BibTeX]

[C] A. Harms, W.U. Bajwa, and R. Calderbank, “Efficient linear time-varying system identification using chirp waveforms,” in Proc. 48th Asilomar Conf. Signals, Systems, and Computers, Pacific Grove, CA, Nov. 2-5, 2014, pp. 854-858. [BibTeX]

[C] A. Harms, W.U. Bajwa, and R. Calderbank, “Resource-efficient parametric recovery of linear time-varying systems,” in Proc. 5th IEEE Intl. Workshop Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP’13), Saint Martin, Dec. 15-18, 2013, pp. 200-203. [BibTeX]

[C] S. Sun, A.P. Petropulu, and W.U. Bajwa, “High-resolution networked MIMO radar based on sub-Nyquist observations,” in Proc. Workshop Signal Processing with Adaptive Sparse Structured Representations (SPARS’13), Lausanne, Switzerland, July 8-11, 2013. [BibTeX]

[C] S. Sun, A.P. Petropulu, and W.U. Bajwa, “Target estimation in colocated MIMO radar via matrix completion,” in Proc. IEEE Intl. Conf. Acoustics, Speech, and Signal Processing (ICASSP’13), Vancouver, Canada, May 26-31, 2013, pp. 4144-4148. [BibTeX]

[J] W.U. Bajwa, K. Gedalyahu, and Y.C. Eldar, “Identification of parametric underspread linear systems and super-resolution radar,” IEEE Trans. Signal Processing, vol. 59, no. 6, pp. 2548-2561, Jun. 2011. [BibTeX]

[C] W.U. Bajwa, K. Gedalyahu, and Y.C. Eldar, “On the identification of parametric underspread linear systems,” in Proc. IEEE Intl. Conf. Acoustics, Speech, and Signal Processing (ICASSP’11), Prague, Czech Republic, May 22-27, 2011, pp. 4088-4091. [BibTeX]

[J] S. Liang, A. Higuera, C. Peters, V. Roy, W.U. Bajwa, H. Shatkay, and C.D. Tunnell, “Domain-informed neural networks for interaction localization within astroparticle experiments,” Front. Artif. Intell. – Big Data and AI in High Energy Physics, vol. 5, pp. 1–12, Jun. 2022. [BibTeX]

[J] A. Nooraiepour, S. Vosoughitabar, C.-S.M. Wu, W.U. Bajwa, and N.B. Mandayam, “Time-varying metamaterial-enabled directional modulation schemes for physical layer security in wireless communication links,” ACM J. Emerg. Technol. Comput. Syst., 2022 (in press). [BibTeX]

[J] A. Nooraiepour, W.U. Bajwa, and N.B. Mandayam, “A hybrid model-based and learning-based approach for classification using limited number of training samples,” IEEE Open J. Signal Proc., vol. 3, pp. 49-70, Jan. 2022. [BibTeX] [IEEE Xplore Version]

[C] A. Nooraiepour, W.U. Bajwa, and N.B. Mandayam, “HyPhyLearn: A domain adaptation-inspired approach to classification using limited number of training samples,” in Proc. IEEE Intl. Workshop Machine Learning for Signal Processing (MLSP’21), Gold Coast, Australia, Oct. 25-28, 2021, pp. 1-6. [BibTeX] [IEEE Xplore Version]

[J] A. Nooraiepour, W.U. Bajwa, and N.B. Mandayam, “Learning-aided physical layer attacks against multicarrier communications in IoT,” IEEE Trans. Cognitive Commun. Netw., vol. 7, no. 1, pp. 239-254, Mar. 2021. [BibTeX] [IEEE Xplore Version]

[C] Z. Shakeri, B.A. Taki, A.L.F. de Almeida, M. Ghassemi, and W.U. Bajwa, “Revisiting sparse channel estimation in massive MIMO-OFDM systems,” in Proc. IEEE Intl. Workshop on Signal Processing Advances in Wireless Communications (SPAWC’19), Cannes, France, Jul. 2-5, 2019, pp. 1-5. [BibTeX]

[C] A. Nooraiepour, K. Hamidouche, W.U. Bajwa, and N. Mandayam, “How secure are multicarrier communication systems against signal exploitation attacks?” in Proc. IEEE Military Communications Conf. (MILCOM’18), Los Angeles, CA, Oct. 29-31, 2018, pp. 201-206. [BibTeX]

[J] M. Elgenedy, M. Mokhtar, R. Hamila, W.U. Bajwa, A.S. Ibrahim, and N. Al-Dhahir, “Sparsity-based joint NBI and impulse noise mitigation in hybrid PLC–wireless transmissions,” IEEE Access, vol. 6, pp. 30280-30295, May 2018. [BibTeX]

[J] A.O. Alabbasi, R. Hamila, W.U. Bajwa, and N. Al-Dhahir, “Design and analysis of sparsifying dictionaries for FIR MIMO equalizers,” IEEE Trans. Wireless Commun., vol. 16, no. 4, pp. 2576-2586, Apr. 2017. [BibTeX]

[C] M. Mokhtar, R. Hamila, W.U. Bajwa, and N. Al-Dhahir, “Deterministic measurement procedures for diagnosis of massive uniform linear antenna arrays,” in Proc. 4th IEEE Global Conf. Signal and Information Processing (GlobalSIP’16), Symposium on Sparse Signal Processing for Communications, Washington, DC, Dec. 7-9, 2016, pp. 1388-1392. [BibTeX]

[C] A.O. Alabbasi, R. Hamila, W.U. Bajwa, and N. Al-Dhahir, “Sparsifying dictionary analysis for FIR MIMO channel-shortening equalizers,” in Proc. IEEE Intl. Workshop on Signal Processing Advances in Wireless Communications (SPAWC’16), Edinburgh, UK, Jul. 3-6, 2016, pp. 1-6. [BibTeX]

[C] A.O. Alabbasi, R. Hamila, W.U. Bajwa, and N. Al-Dhahir, “Design and analysis framework for sparse FIR channel shortening,” in Proc. IEEE Intl. Conf. Communications (ICC’16), Kuala Lumpur, Malaysia, May 23-27, 2016, pp. 1-7. [BibTeX]

[C] A.O. Alabbasi, R. Hamila, W.U. Bajwa, and N. Al-Dhahir, “A general framework for the design and analysis of sparse FIR linear equalizers,” in Proc. 3rd IEEE Global Conf. Signal and Information Processing (GlobalSIP’15), General Symposium, Orlando, FL, Dec. 14-16, 2015, pp. 834-838. [BibTeX]

[C] M. Mokhtar, W.U. Bajwa, M. Elgenedy, and N. Al-Dhahir, “Exploiting block sparsity for joint mitigation of asynchronous NBI and IN in hybrid powerline-wireless communications,” in Proc. IEEE Intl. Conf. Smart Grid Communications (SmartGridComm’15), Miami, FL, Nov. 2-5, 2015, pp. 362-367. [BibTeX]

[J] A. Harms, W.U. Bajwa, and R. Calderbank, “Identification of linear time-varying systems through waveform diversity,” IEEE Trans. Signal Processing, vol. 63, no. 8, pp. 2070-2084, Apr. 2015. [BibTeX]

[C] Z. Shakeri and W.U. Bajwa, “Deterministic selection of pilot tones for compressive estimation of MIMO-OFDM channels,” in Proc. 48th Annu. Conf. Information Sciences and Systems (CISS’15), Baltimore, MD, Mar. 18-20, 2015, pp. 1-6. [BibTeX]

[C] M. Mokhtar, W.U. Bajwa, and N. Al-Dhahir, “Sparsity-aware joint narrowband interference and impulse noise mitigation for hybrid powerline-wireless transmission,” in Proc. IEEE Wireless Communications and Networking Conf. (WCNC’15), New Orleans, LA, Mar. 9-12, 2015, pp. pp. 615-620. [BibTeX]

[C] A. Harms, W.U. Bajwa, and R. Calderbank, “Efficient linear time-varying system identification using chirp waveforms,” in Proc. 48th Asilomar Conf. Signals, Systems, and Computers, Pacific Grove, CA, Nov. 2-5, 2014, pp. 854-858. [BibTeX]

[C] M. Tavan, R.D. Yates, and W.U. Bajwa, “Information in tweets: Analysis of a bufferless timing channel model,” in Proc. IEEE Intl. Symp. Information Theory (ISIT’14), Honolulu, HI, Jun. 29-Jul. 4, 2014, pp. 826-830. [BibTeX]

[C] M. Tavan, R.D. Yates, and W.U. Bajwa, “Capacity analysis of a discrete-time bufferless timing channel,” in Proc. 48th Annu. Conf. Information Sciences and Systems (CISS’14), Princeton, NJ, Mar. 19-21, 2014, pp. 1-6. [BibTeX]

[C] A. Harms, W.U. Bajwa, and R. Calderbank, “Resource-efficient parametric recovery of linear time-varying systems,” in Proc. 5th IEEE Intl. Workshop Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP’13), Saint Martin, Dec. 15-18, 2013, pp. 200-203. [BibTeX]

[C] M. Nokleby and W.U. Bajwa, “Resource tradeoffs in distributed subspace tracking over the wireless medium,” in Proc. 1st IEEE Global Conf. Signal and Information Processing (GlobalSIP’13), Symposium on Network Theory, Austin, TX, Dec. 2013, pp. 823-826. [BibTeX]

[C] M. Tavan, R.D. Yates, and W.U. Bajwa, “Bits through bufferless queues,” in Proc. 51st Annu. Allerton Conf. Communication, Control, and Computing, Monticello, IL, Oct. 2-4, 2013, pp. 755-762. [BibTeX]

[J] M. Nokleby, W.U. Bajwa, R. Calderbank, and B. Aazhang, “Toward resource-optimal consensus over the wireless medium,” IEEE J. Select. Topics Signal Processing, vol. 7, no. 2, pp. 284-295, Apr. 2013. [BibTeX]

[C] M. Nokleby, W.U. Bajwa, R. Calderbank, and B. Aazhang, “Toward resource-optimal averaging consensus over the wireless medium,” in Proc. 46th Asilomar Conf. Signals, Systems, and Computers, Pacific Grove, CA, Nov. 4-7, 2012, pp. 1197-1201. [BibTeX]

[C] A. Harms, W.U. Bajwa, and R. Calderbank, “Rapid sensing of underutilized, wideband spectrum using the random demodulator,” in Proc. 46th Asilomar Conf. Signals, Systems, and Computers, Pacific Grove, CA, Nov. 4-7, 2012, pp. 1940-1944. [BibTeX]

[J] L. Applebaum, W.U. Bajwa, M.F. Duarte, and R. Calderbank, “Asynchronous code-division random access using convex optimization,” Elsevier Phy. Commun., vol. 5, no. 2, pp. 129-147, Jun. 2012. [BibTeX]

[C] M. Nokleby, W.U. Bajwa, R. Calderbank, and B. Aazhang, “Hierarchical averaging over wireless networks,” in Proc. IEEE Intl. Conf. Acoustics, Speech, and Signal Processing (ICASSP’12), Kyoto, Japan, Mar. 25-30, 2012, pp. 3121-3124. [Erratum] [BibTeX]

[C] M. Nokleby, W.U. Bajwa, R. Calderbank, and B. Aazhang, “Gossiping in groups: Distributed averaging over the wireless medium,” in Proc. 49th Annu. Allerton Conf. Communication, Control, and Computing, Monticello, IL, Sep. 28-30, 2011, pp. 1242-1249. [BibTeX]

[C] L. Applebaum, W.U. Bajwa, R. Calderbank, and S. Howard, “Choir codes: Coding for full duplex interference management,” in Proc. 49th Annu. Allerton Conf. Communication, Control, and Computing, Monticello, IL, Sep. 28-30, 2011, pp. 1-8. [BibTeX]

[C] L. Applebaum, W.U. Bajwa, R. Calderbank, J. Haupt, and R. Nowak, “Deterministic pilot sequences for sparse channel estimation in OFDM systems,” in Proc. 17th IEEE Intl. Conf. Digital Signal Processing (DSP’11), Corfu, Greece, Jul. 6-8, 2011. [BibTeX]

[J] J. Haupt, W.U. Bajwa, G. Raz, and R. Nowak, “Toeplitz compressed sensing matrices with applications to sparse channel estimation,” IEEE Trans. Inform. Theory, vol. 56, no. 11, pp. 5862-5875, Nov. 2010. [BibTeX]

[C] L. Applebaum, W.U. Bajwa, M.F. Duarte, and R. Calderbank, “Multiuser detection in asynchronous on–off random access channels using lasso,” in Proc. 48th Annu. Allerton Conf. Communication, Control, and Computing, Monticello, IL, Sep. 29-Oct. 01, 2010, pp. 130-137. [BibTeX]

[J] W.U. Bajwa, J. Haupt, A.M. Sayeed, and R. Nowak, “Compressed channel sensing: A new approach to estimating sparse multipath channels,” Proc. of the IEEE, vol. 98, no. 6, pp. 1058-1076, Jun. 2010. [BibTeX]

[J] J. Haupt, W.U. Bajwa, M. Rabbat, and R. Nowak, “Compressed sensing and network monitoring,” The Next Wave, vol. 18, no. 3, pp. 16-25, 2010. [BibTeX]

[T] W.U. Bajwa, “New information processing theory and methods for exploiting sparsity in wireless systems,” Ph.D. Dissertation, University of Wisconsin-Madison, Madison, WI, 2009. [BibTeX]

[C] W.U. Bajwa, A.M. Sayeed, and R. Nowak, “Sparse multipath channels: Modeling and estimation,” in Proc. 13th IEEE Digital Signal Processing Workshop, Marco Island, FL, Jan. 4-7, 2009, pp. 320-325. [BibTeX]

[C] W.U. Bajwa, A.M. Sayeed, and R. Nowak, “Compressed sensing of wireless channels in time, frequency, and space,” in Proc. 42nd Asilomar Conf. Signals, Systems, and Computers, Pacific Grove, CA, Oct. 26-29, 2008, pp. 2048-2052. [Errata] [BibTeX]

[C] W.U. Bajwa, A.M. Sayeed, and R. Nowak, “Learning sparse doubly-selective channels,” in Proc. 46th Annu. Allerton Conf. Communication, Control, and Computing, Monticello, IL, Sep. 23-26, 2008, pp. 575-582. (Extended Version: UW-Madison Tech. Report ECE-08-02, Jun. 2008) [BibTeX]

[J] J. Haupt, W.U. Bajwa, M. Rabbat, and R. Nowak, “Compressed sensing for networked data,” IEEE Signal Processing Mag., vol. 25, no. 2, pp. 92-101, Mar. 2008. [BibTeX]

[C] W.U. Bajwa, J. Haupt, G. Raz, and R. Nowak, “Compressed channel sensing,” in Proc. 42nd Annu. Conf. Information Sciences and Systems (CISS’08), Princeton, NJ, Mar. 19-21, 2008, pp. 5-10. [BibTeX]

[J] W.U. Bajwa, J. Haupt, A.M. Sayeed, and R. Nowak, “Joint source–channel communication for distributed estimation in sensor networks,” IEEE Trans. Inform. Theory, vol. 53, no. 10, pp. 3629-3653, Oct. 2007. [BibTeX]

[C] J.D. Wierer, W.U. Bajwa, N. Boston, and R. Nowak, “Characterizing decoding robustness under parametric channel uncertainty,” in Proc. 45th Annu. Allerton Conf. Communication, Control, and Computing, Monticello, IL, Sep. 26-28, 2007, pp. 935-939. [BibTeX]

[C] W.U. Bajwa, J. Haupt, A.M. Sayeed, and R. Nowak, “A universal matched source-channel communication scheme for wireless sensor ensembles,” in Proc. IEEE Intl. Conf. Acoustics, Speech, and Signal Processing (ICASSP’06), Toulouse, France, May 14-19, 2006, vol. 5, pp. 1153-1156. [BibTeX]

[C] W.U. Bajwa, J. Haupt, A.M. Sayeed, and R. Nowak, “Compressive wireless sensing,” in Proc. 5th ACM/IEEE Intl. Conf. Information Processing in Sensor Networks (IPSN’06), Nashville, TN, Apr. 19-21, 2006, pp. 134-142 (Acceptance rate: 41/165). [BibTeX]

[C] W.U. Bajwa, A.M. Sayeed, and R. Nowak, “Matched source-channel communication for field estimation in wireless sensor networks,” in Proc. 4th ACM/IEEE Intl. Conf. Information Processing in Sensor Networks (IPSN’05), Los Angeles, CA, Apr. 25-27, 2005, pp. 332-339 (Acceptance rate: 44/213). [BibTeX]

[C] W.U. Bajwa, A.M. Sayeed, and R. Nowak, “Efficient communication strategies for distributed signal field estimation,” in Proc. 38th Asilomar Conf. Signals, Systems, and Computers, Pacific Grove, CA, Nov. 7-10, 2004, pp. 1371-1375. [BibTeX]

[C] W.U. Bajwa, S.A. Ahmed, A. Abbas, S. Zulfiqar, and A. Qayyum, “Mobile IP based mobility management for 3G wireless networks,” in Proc. Intl. Symp. Wireless Systems and Networks (ISWSN’03), Dhahran, Saudi Arabia, Mar. 24-26, 2003.

[J] T. Ahmed, H. Raja, and W.U. Bajwa, “Tensor regression using low-rank and sparse Tucker decompositions,” SIAM J. Math. Data Science, vol. 2, no. 4, pp. 944-966, 2020. [BibTeX] [SIAM Version]

[J] W.U. Bajwa and D. Mixon, “A multiple hypothesis testing approach to low-complexity subspace unmixing,” arXiv preprint. [BibTeX]

[J] J.P. Dumas, M.A. Lodhi, B.A. Taki, W.U. Bajwa, and M.C. Pierce, “Computational endoscopy—A framework for improving spatial resolution in fiber bundle imaging,” Optics Letters, vol. 44, no. 16, pp. 3968-3971, 2019. [BibTeX]

[C] Z. Shakeri, B.A. Taki, A.L.F. de Almeida, M. Ghassemi, and W.U. Bajwa, “Revisiting sparse channel estimation in massive MIMO-OFDM systems,” in Proc. IEEE Intl. Workshop on Signal Processing Advances in Wireless Communications (SPAWC’19), Cannes, France, Jul. 2-5, 2019, pp. 1-5. [BibTeX]

[J] T. Ahmed and W.U. Bajwa, “ExSIS: Extended sure independence screening for ultrahigh-dimensional linear models,” EURASIP J. Signal Processing, vol. 159, pp. 33-48, Jun. 2019. [BibTeX] [Elsevier ScienceDirect Version]

[C] J.P. Dumas, M.A. Lodhi, B.A. Taki, W.U. Bajwa, and M.C. Pierce, “A computational imaging approach for resolution enhancement in fiber bundle endomicroscopy,” in Proc. SPIE Conf. Endoscopic Microscopy XIV, San Francisco, CA, Feb. 2-4, 2019, pp. 1-7. [BibTeX] [SPIE Version]

[J] M. Elgenedy, M. Mokhtar, R. Hamila, W.U. Bajwa, A.S. Ibrahim, and N. Al-Dhahir, “Sparsity-based joint NBI and impulse noise mitigation in hybrid PLC–wireless transmissions,” IEEE Access, vol. 6, pp. 30280-30295, May 2018. [BibTeX]

[C] J.P. Dumas, M.A. Lodhi, W.U. Bajwa, and M.C. Pierce, “A compressed sensing approach for resolution improvement in fiber-bundle based endomicroscopy,” in Proc. SPIE Conf. Endoscopic Microscopy XIII, San Francisco, CA, Jan. 27-29, 2018, pp. 1-7. [BibTeX]

[C] T. Ahmed and W.U. Bajwa, “Correlation-based ultrahigh-dimensional variable screening,” in Proc. 7th IEEE Intl. Workshop Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP’17), Curaçao, Dutch Antilles, Dec. 10-13, 2017, pp. 1-5. [BibTeX] (Winner of Best Student Paper Award)

[J] J.P. Dumas, M.A. Lodhi, W.U. Bajwa, and M.C. Pierce, “From modeling to hardware: An experimental evaluation of image plane and Fourier plane coded compressive optical imaging,” Optics Express, vol. 25, no. 23, pp. 29472-29491, Nov. 2017. [BibTeX]

[J] A.O. Alabbasi, R. Hamila, W.U. Bajwa, and N. Al-Dhahir, “Design and analysis of sparsifying dictionaries for FIR MIMO equalizers,” IEEE Trans. Wireless Commun., vol. 16, no. 4, pp. 2576-2586, Apr. 2017. [BibTeX]

[C] M.A. Lodhi, J.P. Dumas, M.C. Pierce, and W.U. Bajwa, “Computational imaging through a fiber-optic bundle,” in Proc. SPIE Conf. Compressive Sensing VI, Anaheim, CA, Apr. 12-13, 2017, pp. 1-11. [BibTeX]

[C] J.P. Dumas, M.A. Lodhi, W.U. Bajwa, and M.C. Pierce, “Evaluation of computational endomicroscopy architectures for minimally-invasive optical biopsy,” in Proc. SPIE Conf. Endoscopic Microscopy XII, San Francisco, CA, Jan. 29-30, 2017, pp. 1-7. [BibTeX]

[C] M. Mokhtar, R. Hamila, W.U. Bajwa, and N. Al-Dhahir, “Deterministic measurement procedures for diagnosis of massive uniform linear antenna arrays,” in Proc. 4th IEEE Global Conf. Signal and Information Processing (GlobalSIP’16), Symposium on Sparse Signal Processing for Communications, Washington, DC, Dec. 7-9, 2016, pp. 1388-1392. [BibTeX]

[C] A.O. Alabbasi, R. Hamila, W.U. Bajwa, and N. Al-Dhahir, “Sparsifying dictionary analysis for FIR MIMO channel-shortening equalizers,” in Proc. IEEE Intl. Workshop on Signal Processing Advances in Wireless Communications (SPAWC’16), Edinburgh, UK, Jul. 3-6, 2016, pp. 1-6. [BibTeX]

[C] A.O. Alabbasi, R. Hamila, W.U. Bajwa, and N. Al-Dhahir, “Design and analysis framework for sparse FIR channel shortening,” in Proc. IEEE Intl. Conf. Communications (ICC’16), Kuala Lumpur, Malaysia, May 23-27, 2016, pp. 1-7. [BibTeX]

[C] J.P. Dumas, M.C. Pierce, M.A. Lodhi, and W.U. Bajwa, “Design and characterization of a computational endomicroscopy platform for optical biopsy,” in Proc. Biomedical Optics 2016 (Clinical and Translational Biophotonics), Fort Lauderdale, FL, Apr. 25-28, 2016, p. JM3A.37. [BibTeX]

[C] M.A. Lodhi, S. Voronin, and W.U. Bajwa, “YAMPA: Yet another matching pursuit algorithm for compressive sensing,” in Proc. SPIE Defense and Commercial Sensing Conf. Compressive Sensing, Baltimore, MD, Apr. 17-21, 2016, pp. 1-18. [BibTeX]

[J] J.P. Dumas, M.A. Lodhi, W.U. Bajwa, and M.C. Pierce, “Computational imaging with a highly parallel image-plane-coded architecture: Challenges and solutions,” Optics Express, vol. 24, no. 6, pp. 6145-6155, Mar. 2016. [BibTeX]

[C] A.O. Alabbasi, R. Hamila, W.U. Bajwa, and N. Al-Dhahir, “A general framework for the design and analysis of sparse FIR linear equalizers,” in Proc. 3rd IEEE Global Conf. Signal and Information Processing (GlobalSIP’15), General Symposium, Orlando, FL, Dec. 14-16, 2015, pp. 834-838. [BibTeX]

[C] M. Mokhtar, W.U. Bajwa, M. Elgenedy, and N. Al-Dhahir, “Exploiting block sparsity for joint mitigation of asynchronous NBI and IN in hybrid powerline-wireless communications,” in Proc. IEEE Intl. Conf. Smart Grid Communications (SmartGridComm’15), Miami, FL, Nov. 2-5, 2015, pp. 362-367. [BibTeX]

[J] W.U. Bajwa, M.F. Duarte, and R. Calderbank, “Conditioning of random block subdictionaries with applications to block-sparse recovery and regression,” IEEE Trans. Information Theory, vol. 61, no. 7, pp. 4060-4079, Jul. 2015. Companion Code – Download from BitBucket. [BibTeX]

[C] Z. Shakeri and W.U. Bajwa, “Deterministic selection of pilot tones for compressive estimation of MIMO-OFDM channels,” in Proc. 48th Annu. Conf. Information Sciences and Systems (CISS’15), Baltimore, MD, Mar. 18-20, 2015, pp. 1-6. [BibTeX]

[C] M. Mokhtar, W.U. Bajwa, and N. Al-Dhahir, “Sparsity-aware joint narrowband interference and impulse noise mitigation for hybrid powerline-wireless transmission,” in Proc. IEEE Wireless Communications and Networking Conf. (WCNC’15), New Orleans, LA, Mar. 9-12, 2015, pp. pp. 615-620. [BibTeX]

[C] W.U. Bajwa, M.F. Duarte, and R. Calderbank, “Average case analysis of high-dimensional block-sparse recovery and regression for arbitrary designs,” in Proc. 17th Intl. Conf. Artificial Intelligence and Statistics (AISTATS’14), Reykjavik, Iceland, Apr. 22-25, 2014, pp. 57-67 (Acceptance rate: 120/335). [BibTeX]

[C] A. Harms, W.U. Bajwa, and R. Calderbank, “Shaping the power spectra of bipolar sequences with application to sub-Nyquist sampling,” in Proc. 5th IEEE Intl. Workshop Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP’13), Saint Martin, Dec. 15-18, 2013, pp. 236-239. [BibTeX]

[C] S. Sun, A.P. Petropulu, and W.U. Bajwa, “High-resolution networked MIMO radar based on sub-Nyquist observations,” in Proc. Workshop Signal Processing with Adaptive Sparse Structured Representations (SPARS’13), Lausanne, Switzerland, July 8-11, 2013. [BibTeX]

[J] A. Harms, W.U. Bajwa, and R. Calderbank, “A constrained random demodulator for sub-Nyquist sampling,” IEEE Trans. Signal Processing, vol. 61, no. 3, pp. 707-723, Feb. 2013. Companion Code – Download from RunMyCode or GitHub. [BibTeX]

[C] A. Harms, W.U. Bajwa, and R. Calderbank, “Rapid sensing of underutilized, wideband spectrum using the random demodulator,” in Proc. 46th Asilomar Conf. Signals, Systems, and Computers, Pacific Grove, CA, Nov. 4-7, 2012, pp. 1940-1944. [BibTeX]

[C] W.U. Bajwa and D.G. Mixon, “Group model selection using marginal correlations: The good, the bad and the ugly,” in Proc. 50th Annu. Allerton Conf. Communication, Control, and Computing, Monticello, IL, Oct. 1-5, 2012, pp. 494-501. [BibTeX]

[J] W.U. Bajwa, R. Calderbank, and D.G. Mixon, “Two are better than one: Fundamental parameters of frame coherence,” Appl. Comput. Harmon. Anal., vol. 33, no. 1, pp. 58-78, Jul. 2012. [BibTeX]

[J] L. Applebaum, W.U. Bajwa, M.F. Duarte, and R. Calderbank, “Asynchronous code-division random access using convex optimization,” Elsevier Phy. Commun., vol. 5, no. 2, pp. 129-147, Jun. 2012. [BibTeX]

[C] W.U. Bajwa, “Geometry of random Toeplitz-block sensing matrices: Bounds and implications for sparse signal processing,” in Proc. SPIE Defense, Security, and Sensing Conf. Compressive Sensing, Baltimore, MD, Apr. 23-27, 2012, pp. 1-7. [BibTeX]

[B] W.U. Bajwa and A. Pezeshki, “Finite frames for sparse signal processing,” in Finite Frames, P. Casazza and G. Kutyniok, Eds. Cambridge, MA: Birkhäuser Boston, 2012, Ch. 10, pp. 303-335. [BibTeX]

[C] A. Harms, W.U. Bajwa, and R. Calderbank, “Faster than Nyquist, slower than Tropp,” in Proc. 4th IEEE Intl. Workshop Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP’11), San Juan, Puerto Rico, Dec. 13-16, 2011, pp. 345-348. [BibTeX]

[C] D.G. Mixon, W.U. Bajwa, and R. Calderbank, “Frame coherence and sparse signal processing,” in Proc. IEEE Intl. Symp. Information Theory (ISIT’11), Saint-Petersburg, Russia, Jul. 31-Aug. 5, 2011, pp. 663-667. [BibTeX]

[C] L. Applebaum, W.U. Bajwa, R. Calderbank, J. Haupt, and R. Nowak, “Deterministic pilot sequences for sparse channel estimation in OFDM systems,” in Proc. 17th IEEE Intl. Conf. Digital Signal Processing (DSP’11), Corfu, Greece, Jul. 6-8, 2011. [BibTeX]

[J] W.U. Bajwa, K. Gedalyahu, and Y.C. Eldar, “Identification of parametric underspread linear systems and super-resolution radar,” IEEE Trans. Signal Processing, vol. 59, no. 6, pp. 2548-2561, Jun. 2011. [BibTeX]

[C] M.F. Duarte, W.U. Bajwa, and R. Calderbank, “Regression performance of group lasso for arbitrary design matrices,” in Proc. Intl. Conf. Sampling Theory and Applications (SampTA’11), Singapore, May 2-6, 2011. [BibTeX]

[C] W.U. Bajwa, K. Gedalyahu, and Y.C. Eldar, “On the identification of parametric underspread linear systems,” in Proc. IEEE Intl. Conf. Acoustics, Speech, and Signal Processing (ICASSP’11), Prague, Czech Republic, May 22-27, 2011, pp. 4088-4091. [BibTeX]

[C] A. Harms, W.U. Bajwa, and R. Calderbank, “Beating Nyquist through correlations: A constrained random demodulator for sampling of sparse bandlimited signals,” in Proc. IEEE Intl. Conf. Acoustics, Speech, and Signal Processing (ICASSP’11), Prague, Czech Republic, May 22-27, 2011, pp. 5968-5971. [BibTeX]

[J] J. Haupt, W.U. Bajwa, G. Raz, and R. Nowak, “Toeplitz compressed sensing matrices with applications to sparse channel estimation,” IEEE Trans. Inform. Theory, vol. 56, no. 11, pp. 5862-5875, Nov. 2010. [BibTeX]

[C] W.U. Bajwa, R. Calderbank, and S. Jafarpour, “Revisiting model selection and recovery of sparse signals using one-step thresholding,” in Proc. 48th Annu. Allerton Conf. Communication, Control, and Computing, Monticello, IL, Sep. 29-Oct. 01, 2010, pp. 977-984. [BibTeX]

[C] L. Applebaum, W.U. Bajwa, M.F. Duarte, and R. Calderbank, “Multiuser detection in asynchronous on–off random access channels using lasso,” in Proc. 48th Annu. Allerton Conf. Communication, Control, and Computing, Monticello, IL, Sep. 29-Oct. 01, 2010, pp. 130-137. [BibTeX]

[J] W.U. Bajwa, R. Calderbank, and S. Jafarpour, “Why Gabor frames? Two fundamental measures of coherence and their role in model selection,” J. Commun. Netw., vol. 12, no. 4, pp. 289-307, Aug. 2010. [BibTeX]

[J] W.U. Bajwa, J. Haupt, A.M. Sayeed, and R. Nowak, “Compressed channel sensing: A new approach to estimating sparse multipath channels,” Proc. of the IEEE, vol. 98, no. 6, pp. 1058-1076, Jun. 2010. [BibTeX]

[C] W.U. Bajwa, R. Calderbank, and S. Jafarpour, “Model selection: Two fundamental measures of coherence and their algorithmic significance,” in Proc. IEEE Intl. Symp. Information Theory (ISIT’10), Austin, TX, Jun. 13-18, 2010, pp. 1568-1572. [BibTeX]

[J] J. Haupt, W.U. Bajwa, M. Rabbat, and R. Nowak, “Compressed sensing and network monitoring,” The Next Wave, vol. 18, no. 3, pp. 16-25, 2010. [BibTeX]

[C] W.U. Bajwa, A.M. Sayeed, and R. Nowak, “A restricted isometry property for structurally-subsampled unitary matrices,” in Proc. 47th Annu. Allerton Conf. Communication, Control, and Computing, Monticello, IL, Sep. 30-Oct. 02, 2009, pp. 1005-1012. [BibTeX]

[T] W.U. Bajwa, “New information processing theory and methods for exploiting sparsity in wireless systems,” Ph.D. Dissertation, University of Wisconsin-Madison, Madison, WI, 2009. [BibTeX]

[C] W.U. Bajwa, A.M. Sayeed, and R. Nowak, “Sparse multipath channels: Modeling and estimation,” in Proc. 13th IEEE Digital Signal Processing Workshop, Marco Island, FL, Jan. 4-7, 2009, pp. 320-325. [BibTeX]

[C] W.U. Bajwa, A.M. Sayeed, and R. Nowak, “Compressed sensing of wireless channels in time, frequency, and space,” in Proc. 42nd Asilomar Conf. Signals, Systems, and Computers, Pacific Grove, CA, Oct. 26-29, 2008, pp. 2048-2052. [Errata] [BibTeX]

[C] W.U. Bajwa, A.M. Sayeed, and R. Nowak, “Learning sparse doubly-selective channels,” in Proc. 46th Annu. Allerton Conf. Communication, Control, and Computing, Monticello, IL, Sep. 23-26, 2008, pp. 575-582. (Extended Version: UW-Madison Tech. Report ECE-08-02, Jun. 2008) [BibTeX]

[J] J. Haupt, W.U. Bajwa, M. Rabbat, and R. Nowak, “Compressed sensing for networked data,” IEEE Signal Processing Mag., vol. 25, no. 2, pp. 92-101, Mar. 2008. [BibTeX]

[C] W.U. Bajwa, J. Haupt, G. Raz, and R. Nowak, “Compressed channel sensing,” in Proc. 42nd Annu. Conf. Information Sciences and Systems (CISS’08), Princeton, NJ, Mar. 19-21, 2008, pp. 5-10. [BibTeX]

[J] W.U. Bajwa, J. Haupt, A.M. Sayeed, and R. Nowak, “Joint source–channel communication for distributed estimation in sensor networks,” IEEE Trans. Inform. Theory, vol. 53, no. 10, pp. 3629-3653, Oct. 2007. [BibTeX]

[C] W.U. Bajwa, J. Haupt, G. Raz, S.J. Wright, and R. Nowak, “Toeplitz-structured compressed sensing matrices,” in Proc. 14th IEEE/SP Workshop Statistical Signal Processing (SSP’07), Madison, WI, Aug. 26-29, 2007, pp. 294-298 (Acceptance rate: 185/262). [BibTeX]

[C] W.U. Bajwa, J. Haupt, A.M. Sayeed, and R. Nowak, “A universal matched source-channel communication scheme for wireless sensor ensembles,” in Proc. IEEE Intl. Conf. Acoustics, Speech, and Signal Processing (ICASSP’06), Toulouse, France, May 14-19, 2006, vol. 5, pp. 1153-1156. [BibTeX]

[C] W.U. Bajwa, J. Haupt, A.M. Sayeed, and R. Nowak, “Compressive wireless sensing,” in Proc. 5th ACM/IEEE Intl. Conf. Information Processing in Sensor Networks (IPSN’06), Nashville, TN, Apr. 19-21, 2006, pp. 134-142 (Acceptance rate: 41/165). [BibTeX]

[B] Z. Shakeri, A.D. Sarwate, and W.U. Bajwa, “Sample complexity bounds for dictionary learning from vector- and tensor-valued data,” in Information-Theoretic Methods in Data Science, M.R.D. Rodrigues and Y.C. Eldar, Eds. Cambridge, UK: Cambridge University Press, 2021, Ch. 5, pp. 134-162. [BibTeX]

[J] T. Ahmed, H. Raja, and W.U. Bajwa, “Tensor regression using low-rank and sparse Tucker decompositions,” SIAM J. Math. Data Science, vol. 2, no. 4, pp. 944-966, 2020. [BibTeX] [SIAM Version]

[J] M. Ghassemi, Z. Shakeri, A.D. Sarwate, and W.U. Bajwa, “Learning mixtures of separable dictionaries for tensor data: Analysis and algorithms,” IEEE Trans. Signal Processing, vol. 68, pp. 33-48, 2020. Companion Code – DOI: 10.5281/zenodo.3901852. [BibTeX] [Code BibTeX] [IEEE Xplore Version]

[C] M. Ghassemi, Z. Shakeri, A.D. Sarwate, and W.U. Bajwa, “Sample complexity bounds for low-separation-rank dictionary learning,” in Proc. IEEE Intl. Symp. Information Theory (ISIT’19), Paris, France, Jul. 7-12, 2019, pp. 2294-2298. [BibTeX] [IEEE Xplore Version]

[J] Z. Shakeri, A.D. Sarwate, and W.U. Bajwa, “Identifiability of Kronecker-structured dictionaries for tensor data,” IEEE J. Sel. Topics Signal Processing, , vol. 12, no. 5, pp. 1047-1062, Oct. 2018. [BibTeX]

[J] T. Wu and W.U. Bajwa, “A low tensor-rank representation approach for clustering of imaging data,” IEEE Signal Processing Letters, vol. 25, no. 8, pp. 1196-1200, Aug. 2018. [BibTeX]

[J] Z. Shakeri, W.U. Bajwa, and A.D. Sarwate, “Minimax lower bounds on dictionary learning for tensor data,” IEEE Trans. Inform. Theory, vol. 64, no. 4, pp. 2706-2726, Apr. 2018. [BibTeX]

[C] Z. Shakeri, A.D. Sarwate, and W.U. Bajwa, “Identification of Kronecker-structured dictionaries: An asymptotic analysis,” in Proc. 7th IEEE Intl. Workshop Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP’17), Curaçao, Dutch Antilles, Dec. 10-13, 2017, pp. 1-5. [BibTeX]

[C] M. Ghassemi, Z. Shakeri, A.D. Sarwate, and W.U. Bajwa, “STARK: Structured dictionary learning through rank-one tensor recovery,” in Proc. 7th IEEE Intl. Workshop Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP’17), Curaçao, Dutch Antilles, Dec. 10-13, 2017, pp. 1-5. [BibTeX]

[C] Z. Shakeri, W.U. Bajwa, and A.D. Sarwate, “Minimax lower bounds for dictionary learning from tensor data,” in Proc. Workshop Signal Processing with Adaptive Sparse Structured Representations (SPARS’17), Lisbon, Portugal, Jun. 5-8, 2017. [BibTeX]

[C] Z. Shakeri, W.U. Bajwa, and A.D. Sarwate, “Sample complexity bounds for dictionary learning of tensor data,” in Proc. IEEE Intl. Conf. Acoustics, Speech, and Signal Processing (ICASSP’17), New Orleans, LA, Mar. 5-9, 2017, pp. 4501-4505. [BibTeX]

[C] Z. Shakeri, W.U. Bajwa, and A.D. Sarwate, “Minimax lower bounds for Kronecker-structured dictionary learning,” in Proc. IEEE Intl. Symp. Information Theory (ISIT’16), Barcelona, Spain, Jul. 10-15, 2016, pp. 1148-1152. [BibTeX]

[C] W.U. Bajwa, S.A. Ahmed, A. Abbas, and H.A. Qadeer, “Modeling of processor delay and overall reduction in network latencies for real time, interactive applications,” in Proc. IEEE Students Conf. (ISCON’02), Lahore, Pakistan, Aug. 16-17, 2002, vol. 1, pp. 76-79.

[C] W.U. Bajwa, S.A. Ahmed, A. Abbas, and H.A. Qadeer, “A novel design of a generational garbage collector,” in Proc. IEEE Students Conf. (ISCON’02), Lahore, Pakistan, Aug. 16-17, 2002, vol. 1, pp. 85-88.

[C] A. Abbas, A. Ahmed, S.A. Ahmed, W.U. Bajwa, A. Anwar, and S. Abbasi, “A retargetable tool-suite for the design of application specific instruction set processors using a machine description language,” in Proc. IEEE Intl. Symp. Circuits and Systems (ISCAS’02), Scottsdale, AZ, May 26-29, 2002, vol. 1, pp. 425-428.

[C] W.U. Bajwa, H.A. Qadeer, and M. Farooq, “Object-oriented design of a cycle accurate re-configurable simulator toolkit for DSP processors,” in Proc. IEEE Intl. Multi-Topic Conf. (INMIC’01), Lahore, Pakistan, Dec. 28-30, 2001, pp. 10-15.

[T] T. Wu, P. Gurram, R.M. Rao, and W.U. Bajwa, “Human action attribute learning from video data using low-rank representations,” Technical Report 2020-07-001, Department of Electrical and Computer Engineering, Rutgers University, New Brunswick, NJ, Jul. 2020. [BibTeX]

[J] W.U. Bajwa and D. Mixon, “A multiple hypothesis testing approach to low-complexity subspace unmixing,” arXiv preprint. [BibTeX]

[J] M.A. Lodhi and W.U. Bajwa, “Detection theory for union of subspaces,” IEEE Trans. Signal Processing, vol. 66, no. 24, pp. 6347-6362, Dec. 2018. [BibTeX]

[J] T. Wu and W.U. Bajwa, “A low tensor-rank representation approach for clustering of imaging data,” IEEE Signal Processing Letters, vol. 25, no. 8, pp. 1196-1200, Aug. 2018. [BibTeX]

[C] M.A. Lodhi and W.U. Bajwa, “Union of subspaces signal detection in subspace interference,” in Proc. IEEE Workshop Statistical Signal Processing (SSP’18), Freiburg, Germany, Jun. 10-13, 2018, pp. 548-552. [BibTeX]

[C] T. Wu, P. Gurram, R.M. Rao, and W.U. Bajwa, “Human action attribute learning using low-rank representations,” in Proc. Workshop Signal Processing with Adaptive Sparse Structured Representations (SPARS’17), Lisbon, Portugal, Jun. 5-8, 2017. [BibTeX]

[C] T. Wu, P. Gurram, R.M. Rao, and W.U. Bajwa, “Clustering-aware structure-constrained low-rank representation model for learning human action attributes,” in Proc. IEEE Intl. Workshop on Image, Video and Multidimensional Signal Processing (IVMSP’16), Bordeaux, France, Jul. 11-12, 2016, pp. 1-5. [BibTeX] (Winner of the Best Student Paper Award)

[J] T. Wu and W.U. Bajwa, “Learning the nonlinear geometry of high-dimensional data: Models and algorithms,” IEEE Trans. Signal Processing, vol. 63, no. 23, pp. 6229-6244, Dec. 2015. Companion Code – Download from BitBucket. [BibTeX]

[C] T. Wu, P. Gurram, R.M. Rao, and W.U. Bajwa, “Hierarchical union-of-subspaces model for human activity summarization,” in Proc. IEEE Intl. Conf. Computer Vision, Workshop on Video Summarization for Large-Scale Analytics, Santiago, Chile, Dec. 11-18, 2015, pp. 1053-1061. [BibTeX]

[C] T. Wu and W.U. Bajwa, “Metric-constrained kernel union of subspaces,” in Proc. IEEE Intl. Conf. Acoustics, Speech, and Signal Processing (ICASSP’15), Brisbane, Australia, Apr. 19-24, 2015, pp. 5778-5782. [BibTeX]

[C] T. Ahmed and W.U. Bajwa, “Geometric manifold approximation using union of tangent patches,” in Proc. 2nd IEEE Global Conf. Signal and Information Processing (GlobalSIP’14), Symposium on Information Processing for Big Data, Atlanta, GA, Dec. 3-5, 2014, pp. 458-462. [BibTeX]

[C] T. Ahmed and W.U. Bajwa, “A greedy, adaptive approach to learning geometry of nonlinear manifolds,” in Proc. IEEE Workshop Statistical Signal Processing (SSP’14), Gold Coast, Australia, Jun. 29-Jul. 2, 2014, pp. 133-136. [BibTeX]

[C] T. Wu and W.U. Bajwa, “Revisiting robustness of the union-of-subspaces model for data-adaptive learning of nonlinear signal models,” in Proc. IEEE Intl. Conf. Acoustics, Speech, and Signal Processing (ICASSP’14), Florence, Italy, May 4-9, 2014, pp. 3390-3394. [BibTeX]

[J28] M.A. Lodhi and W.U. Bajwa, “Detection theory for union of subspaces,” IEEE Trans. Signal Processing, vol. 66, no. 24, pp. 6347-6362, Dec. 2018. [BibTeX]

[J27] Z. Shakeri, A.D. Sarwate, and W.U. Bajwa, “Identifiability of Kronecker-structured dictionaries for tensor data,” IEEE J. Sel. Topics Signal Processing, , vol. 12, no. 5, pp. 1047-1062, Oct. 2018. [BibTeX]

[J26] T. Wu and W.U. Bajwa, “A low tensor-rank representation approach for clustering of imaging data,” IEEE Signal Processing Letters, vol. 25, no. 8, pp. 1196-1200, Aug. 2018. [BibTeX]

[J25] M. Elgenedy, M. Mokhtar, R. Hamila, W.U. Bajwa, A.S. Ibrahim, and N. Al-Dhahir, “Sparsity-based joint NBI and impulse noise mitigation in hybrid PLC–wireless transmissions,” IEEE Access, vol. 6, pp. 30280-30295, May 2018. [BibTeX]

[J24] Z. Shakeri, W.U. Bajwa, and A.D. Sarwate, “Minimax lower bounds on dictionary learning for tensor data,” IEEE Trans. Inform. Theory, vol. 64, no. 4, pp. 2706-2726, Apr. 2018. [BibTeX]

[J23] J.P. Dumas, M.A. Lodhi, W.U. Bajwa, and M.C. Pierce, “From modeling to hardware: An experimental evaluation of image plane and Fourier plane coded compressive optical imaging,” Optics Express, vol. 25, no. 23, pp. 29472-29491, Nov. 2017. [BibTeX]

[J22] W.U. Bajwa, “On flipping a large signal processing class,” IEEE Signal Processing Mag., vol. 34, no. 4, pp. 158-170, Jul. 2017. [BibTeX]

[J21] A.O. Alabbasi, R. Hamila, W.U. Bajwa, and N. Al-Dhahir, “Design and analysis of sparsifying dictionaries for FIR MIMO equalizers,” IEEE Trans. Wireless Commun., vol. 16, no. 4, pp. 2576-2586, Apr. 2017. [BibTeX]

[J20] S. Parlak, I. Marsic, A. Sarcevic, W.U. Bajwa, L. Waterhouse, and R. Burd, “Passive RFID for object and use detection during trauma resuscitation,” IEEE Trans. Mobile Computing, vol. 15, no. 4, pp. 924-937, Apr. 2016. [BibTeX]

[J19] J.P. Dumas, M.A. Lodhi, W.U. Bajwa, and M.C. Pierce, “Computational imaging with a highly parallel image-plane-coded architecture: Challenges and solutions,” Optics Express, vol. 24, no. 6, pp. 6145-6155, Mar. 2016. [BibTeX]

[J18] H. Raja and W.U. Bajwa, “Cloud K-SVD: A collaborative dictionary learning algorithm for big, distributed data,” IEEE Trans. Signal Processing, vol. 64, no. 1, pp. 173-188, Jan. 2016. Companion Code – Download from BitBucket. [BibTeX]

[J17] T. Wu and W.U. Bajwa, “Learning the nonlinear geometry of high-dimensional data: Models and algorithms,” IEEE Trans. Signal Processing, vol. 63, no. 23, pp. 6229-6244, Dec. 2015. Companion Code – Download from BitBucket. [BibTeX]

[J16] W.U. Bajwa, M.F. Duarte, and R. Calderbank, “Conditioning of random block subdictionaries with applications to block-sparse recovery and regression,” IEEE Trans. Information Theory, vol. 61, no. 7, pp. 4060-4079, Jul. 2015. Companion Code – Download from BitBucket. [BibTeX]

[J15] S. Sun, W.U. Bajwa, and A.P. Petropulu, “MIMO-MC radar: A MIMO radar approach based on matrix completion,” IEEE Trans. Aerosp. Electron. Syst., vol. 51, no. 3, pp. 1839-1852, Jul. 2015. [BibTeX]

[J14] A. Harms, W.U. Bajwa, and R. Calderbank, “Identification of linear time-varying systems through waveform diversity,” IEEE Trans. Signal Processing, vol. 63, no. 8, pp. 2070-2084, Apr. 2015. [BibTeX]

[J13] A. Armagan, D.B. Dunson, J. Lee, W.U. Bajwa, and N. Strawn, “Posterior consistency in linear models under shrinkage priors,” Biometrika, vol. 100, no. 4, pp. 1011-1018, Dec. 2013. [BibTeX]

[J12] K. Krishnamurthy, W.U. Bajwa, and R. Willett, “Level set estimation from projection measurements: Performance guarantees and fast computation,” SIAM J. Imaging Sciences, vol. 6, no. 4, pp. 2047-2074, Oct. 2013. [BibTeX]

[J11] M. Nokleby, W.U. Bajwa, R. Calderbank, and B. Aazhang, “Toward resource-optimal consensus over the wireless medium,” IEEE J. Select. Topics Signal Processing, vol. 7, no. 2, pp. 284-295, Apr. 2013. [BibTeX]

[J10] A. Harms, W.U. Bajwa, and R. Calderbank, “A constrained random demodulator for sub-Nyquist sampling,” IEEE Trans. Signal Processing, vol. 61, no. 3, pp. 707-723, Feb. 2013. Companion Code – Download from RunMyCode or GitHub. [BibTeX]

[J9] W.U. Bajwa, R. Calderbank, and D.G. Mixon, “Two are better than one: Fundamental parameters of frame coherence,” Appl. Comput. Harmon. Anal., vol. 33, no. 1, pp. 58-78, Jul. 2012. [BibTeX]

[J8] L. Applebaum, W.U. Bajwa, M.F. Duarte, and R. Calderbank, “Asynchronous code-division random access using convex optimization,” Elsevier Phy. Commun., vol. 5, no. 2, pp. 129-147, Jun. 2012. [BibTeX]

[J7] W.U. Bajwa, K. Gedalyahu, and Y.C. Eldar, “Identification of parametric underspread linear systems and super-resolution radar,” IEEE Trans. Signal Processing, vol. 59, no. 6, pp. 2548-2561, Jun. 2011. [BibTeX]

[J6] J. Haupt, W.U. Bajwa, G. Raz, and R. Nowak, “Toeplitz compressed sensing matrices with applications to sparse channel estimation,” IEEE Trans. Inform. Theory, vol. 56, no. 11, pp. 5862-5875, Nov. 2010. [BibTeX]

[J5] W.U. Bajwa, R. Calderbank, and S. Jafarpour, “Why Gabor frames? Two fundamental measures of coherence and their role in model selection,” J. Commun. Netw., vol. 12, no. 4, pp. 289-307, Aug. 2010. [BibTeX]

[J4] W.U. Bajwa, J. Haupt, A.M. Sayeed, and R. Nowak, “Compressed channel sensing: A new approach to estimating sparse multipath channels,” Proc. of the IEEE, vol. 98, no. 6, pp. 1058-1076, Jun. 2010. [BibTeX]

[J3] J. Haupt, W.U. Bajwa, M. Rabbat, and R. Nowak, “Compressed sensing and network monitoring,” The Next Wave, vol. 18, no. 3, pp. 16-25, 2010. [BibTeX]

[J2] J. Haupt, W.U. Bajwa, M. Rabbat, and R. Nowak, “Compressed sensing for networked data,” IEEE Signal Processing Mag., vol. 25, no. 2, pp. 92-101, Mar. 2008. [BibTeX]

[J1] W.U. Bajwa, J. Haupt, A.M. Sayeed, and R. Nowak, “Joint source–channel communication for distributed estimation in sensor networks,” IEEE Trans. Inform. Theory, vol. 53, no. 10, pp. 3629-3653, Oct. 2007. [BibTeX]

[C87] A. Nooraiepour, K. Hamidouche, W.U. Bajwa, and N. Mandayam, “How secure are multicarrier communication systems against signal exploitation attacks?” in Proc. IEEE Military Communications Conf. (MILCOM’18), Los Angeles, CA, Oct. 29-31, 2018, pp. 201-206. [BibTeX]

[C86] P. Pandey, M. Rahmati, D. Pompili, and W.U. Bajwa, “Robust distributed dictionary learning for in-network image compression,” in Proc. IEEE Intl. Conf. Autonomic Computing (ICAC’18), Trento, Italy, Sep. 3-7, 2018, pp. 61-70. [BibTeX]

[C85] M.A. Lodhi and W.U. Bajwa, “Union of subspaces signal detection in subspace interference,” in Proc. IEEE Workshop Statistical Signal Processing (SSP’18), Freiburg, Germany, Jun. 10-13, 2018, pp. 548-552. [BibTeX]

[C84] Z. Yang and W.U. Bajwa, “ByRDiE: A Byzantine-resilient distributed learning algorithm,” in Proc. IEEE Data Science Workshop (DSW’18), Lausanne, Switzerland, Jun. 4-6, 2018, pp. 21-25. [BibTeX]

[C83] W.U. Bajwa, “Flipping large classes on a shoestring budget,” in Proc. IEEE Intl. Conf. Acoustics, Speech, and Signal Processing (ICASSP’18), Calgary, Canada, Apr. 15-20, 2018, pp. 7006-7010. [BibTeX]

[C82] A. Burns and W.U. Bajwa, “Multispectral imaging for improved liquid classification in security sensor systems,” in Proc. SPIE Conf. Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXIV, Orlando, FL, Apr. 17-19, 2018, pp. 1-7. [BibTeX]

[C81] J.P. Dumas, M.A. Lodhi, W.U. Bajwa, and M.C. Pierce, “A compressed sensing approach for resolution improvement in fiber-bundle based endomicroscopy,” in Proc. SPIE Conf. Endoscopic Microscopy XIII, San Francisco, CA, Jan. 27-29, 2018, pp. 1-7. [BibTeX]

[C80] T. Ahmed and W.U. Bajwa, “Correlation-based ultrahigh-dimensional variable screening,” in Proc. 7th IEEE Intl. Workshop Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP’17), Curaçao, Dutch Antilles, Dec. 10-13, 2017, pp. 1-5. [BibTeX] (Winner of Best Student Paper Award)

[C79] Z. Shakeri, A.D. Sarwate, and W.U. Bajwa, “Identification of Kronecker-structured dictionaries: An asymptotic analysis,” in Proc. 7th IEEE Intl. Workshop Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP’17), Curaçao, Dutch Antilles, Dec. 10-13, 2017, pp. 1-5. [BibTeX]

[C78] M. Ghassemi, Z. Shakeri, A.D. Sarwate, and W.U. Bajwa, “STARK: Structured dictionary learning through rank-one tensor recovery,” in Proc. 7th IEEE Intl. Workshop Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP’17), Curaçao, Dutch Antilles, Dec. 10-13, 2017, pp. 1-5. [BibTeX]

[C77] M. Nokleby and W.U. Bajwa, “Distributed mirror descent for stochastic learning over rate-limited networks,” in Proc. 7th IEEE Intl. Workshop Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP’17), Curaçao, Dutch Antilles, Dec. 10-13, 2017, pp. 1-5. [BibTeX]

[C76] H. Raja, W.U. Bajwa, and F. Ahmad, “Through-the-wall radar imaging using a distributed quasi-Newton method,” in Proc. 51st Asilomar Conf. Signals, Systems, and Computers, Pacific Grove, CA, Oct. 29-Nov. 1, 2017, pp. 85-89. [BibTeX]

[C75] R. Pilgrim, J. Zhu, D. Baron, and W.U. Bajwa, “Generalized geometric programming for rate allocation in consensus,” in Proc. 55th Annu. Allerton Conf. Communication, Control, and Computing, Monticello, IL, Oct. 4-6, 2017, pp. 374-381. [BibTeX]

[C74] T. Wu, P. Gurram, R.M. Rao, and W.U. Bajwa, “Human action attribute learning using low-rank representations,” in Proc. Workshop Signal Processing with Adaptive Sparse Structured Representations (SPARS’17), Lisbon, Portugal, Jun. 5-8, 2017. [BibTeX]

[C73] Z. Shakeri, W.U. Bajwa, and A.D. Sarwate, “Minimax lower bounds for dictionary learning from tensor data,” in Proc. Workshop Signal Processing with Adaptive Sparse Structured Representations (SPARS’17), Lisbon, Portugal, Jun. 5-8, 2017. [BibTeX]

[C72] M.A. Lodhi, J.P. Dumas, M.C. Pierce, and W.U. Bajwa, “Computational imaging through a fiber-optic bundle,” in Proc. SPIE Conf. Compressive Sensing VI, Anaheim, CA, Apr. 12-13, 2017, pp. 1-11. [BibTeX]

[C71] Z. Shakeri, W.U. Bajwa, and A.D. Sarwate, “Sample complexity bounds for dictionary learning of tensor data,” in Proc. IEEE Intl. Conf. Acoustics, Speech, and Signal Processing (ICASSP’17), New Orleans, LA, Mar. 5-9, 2017, pp. 4501-4505. [BibTeX]

[C70] J.P. Dumas, M.A. Lodhi, W.U. Bajwa, and M.C. Pierce, “Evaluation of computational endomicroscopy architectures for minimally-invasive optical biopsy,” in Proc. SPIE Conf. Endoscopic Microscopy XII, San Francisco, CA, Jan. 29-30, 2017, pp. 1-7. [BibTeX]

[C69] M. Mokhtar, R. Hamila, W.U. Bajwa, and N. Al-Dhahir, “Deterministic measurement procedures for diagnosis of massive uniform linear antenna arrays,” in Proc. 4th IEEE Global Conf. Signal and Information Processing (GlobalSIP’16), Symposium on Sparse Signal Processing for Communications, Washington, DC, Dec. 7-9, 2016, pp. 1388-1392. [BibTeX]

[C68] Z. Shakeri, W.U. Bajwa, and A.D. Sarwate, “Minimax lower bounds for Kronecker-structured dictionary learning,” in Proc. IEEE Intl. Symp. Information Theory (ISIT’16), Barcelona, Spain, Jul. 10-15, 2016, pp. 1148-1152. [BibTeX]

[C67] Z. Shakeri and W.U. Bajwa, “Revisiting maximal response-based local identification of overcomplete dictionaries,” in Proc. IEEE Intl. Workshop on Sensor Array and Multichannel Signal Processing (SAM’16), Rio de Janeiro, Brazil, Jul. 10-13, 2016, pp. 1-5. [BibTeX]

[C66] T. Wu, P. Gurram, R.M. Rao, and W.U. Bajwa, “Clustering-aware structure-constrained low-rank representation model for learning human action attributes,” in Proc. IEEE Intl. Workshop on Image, Video and Multidimensional Signal Processing (IVMSP’16), Bordeaux, France, Jul. 11-12, 2016, pp. 1-5. [BibTeX] (Winner of the Best Student Paper Award)

[C65] A.O. Alabbasi, R. Hamila, W.U. Bajwa, and N. Al-Dhahir, “Sparsifying dictionary analysis for FIR MIMO channel-shortening equalizers,” in Proc. IEEE Intl. Workshop on Signal Processing Advances in Wireless Communications (SPAWC’16), Edinburgh, UK, Jul. 3-6, 2016, pp. 1-6. [BibTeX]

[C64] A.O. Alabbasi, R. Hamila, W.U. Bajwa, and N. Al-Dhahir, “Design and analysis framework for sparse FIR channel shortening,” in Proc. IEEE Intl. Conf. Communications (ICC’16), Kuala Lumpur, Malaysia, May 23-27, 2016, pp. 1-7. [BibTeX]

[C63] H. Raja, W.U. Bajwa, F. Ahmad, and M.G. Amin, “Parametric dictionary learning for TWRI using distributed particle swarm optimization,” in Proc. IEEE Radar Conf., Philadelphia, PA, May 2-6, 2016, pp. 1-5. [BibTeX]

[C62] J.P. Dumas, M.C. Pierce, M.A. Lodhi, and W.U. Bajwa, “Design and characterization of a computational endomicroscopy platform for optical biopsy,” in Proc. Biomedical Optics 2016 (Clinical and Translational Biophotonics), Fort Lauderdale, FL, Apr. 25-28, 2016, p. JM3A.37. [BibTeX]

[C61] M.A. Lodhi, S. Voronin, and W.U. Bajwa, “YAMPA: Yet another matching pursuit algorithm for compressive sensing,” in Proc. SPIE Defense and Commercial Sensing Conf. Compressive Sensing, Baltimore, MD, Apr. 17-21, 2016, pp. 1-18. [BibTeX]

[C60] H. Raja and W.U. Bajwa, “Learning overcomplete representations from distributed data: A brief review,” in Proc. SPIE Defense and Commercial Sensing Conf. Compressive Sensing, Baltimore, MD, Apr. 17-21, 2016, pp. 1-14. [BibTeX]

[C59] Z. Yang and W.U. Bajwa, “RD-SVM: A resilient distributed support vector machine,” in Proc. IEEE Intl. Conf. Acoustics, Speech, and Signal Processing (ICASSP’16), Shanghai, China, Mar. 20-25, 2016, pp. 2444-2448. [BibTeX]

[C58] T. Wu, P. Gurram, R.M. Rao, and W.U. Bajwa, “Hierarchical union-of-subspaces model for human activity summarization,” in Proc. IEEE Intl. Conf. Computer Vision, Workshop on Video Summarization for Large-Scale Analytics, Santiago, Chile, Dec. 11-18, 2015, pp. 1053-1061. [BibTeX]

[C57] A.O. Alabbasi, R. Hamila, W.U. Bajwa, and N. Al-Dhahir, “A general framework for the design and analysis of sparse FIR linear equalizers,” in Proc. 3rd IEEE Global Conf. Signal and Information Processing (GlobalSIP’15), General Symposium, Orlando, FL, Dec. 14-16, 2015, pp. 834-838. [BibTeX]

[C56] M. Mokhtar, W.U. Bajwa, M. Elgenedy, and N. Al-Dhahir, “Exploiting block sparsity for joint mitigation of asynchronous NBI and IN in hybrid powerline-wireless communications,” in Proc. IEEE Intl. Conf. Smart Grid Communications (SmartGridComm’15), Miami, FL, Nov. 2-5, 2015, pp. 362-367. [BibTeX]

[C55] H. Raja and W.U. Bajwa, “A convergence analysis of distributed dictionary learning based on the K-SVD algorithm,” in Proc. IEEE Intl. Symp. Information Theory (ISIT’15), Hong Kong, Jun. 14-19, 2015, pp. 2186-2190. [BibTeX]

[C54] T. Wu and W.U. Bajwa, “Metric-constrained kernel union of subspaces,” in Proc. IEEE Intl. Conf. Acoustics, Speech, and Signal Processing (ICASSP’15), Brisbane, Australia, Apr. 19-24, 2015, pp. 5778-5782. [BibTeX]

[C53] T. Wu, A. Sarwate, and W.U. Bajwa, “Active dictionary learning for image representation,” in Proc. SPIE Unmanned Systems Technology XVII, Baltimore, MD, Apr. 21-23, 2015, pp. 1-10. [BibTeX]

[C52] Z. Shakeri and W.U. Bajwa, “Deterministic selection of pilot tones for compressive estimation of MIMO-OFDM channels,” in Proc. 48th Annu. Conf. Information Sciences and Systems (CISS’15), Baltimore, MD, Mar. 18-20, 2015, pp. 1-6. [BibTeX]

[C51] M. Mokhtar, W.U. Bajwa, and N. Al-Dhahir, “Sparsity-aware joint narrowband interference and impulse noise mitigation for hybrid powerline-wireless transmission,” in Proc. IEEE Wireless Communications and Networking Conf. (WCNC’15), New Orleans, LA, Mar. 9-12, 2015, pp. pp. 615-620. [BibTeX]

[C50] Z. Shakeri, H. Raja, and W.U. Bajwa, “Dictionary learning based nonlinear classifier training from distributed data,” in Proc. 2nd IEEE Global Conf. Signal and Information Processing (GlobalSIP’14), Symposium on Network Theory, Atlanta, GA, Dec. 3-5, 2014, pp. 759-763. [BibTeX]

[C49] T. Ahmed and W.U. Bajwa, “Geometric manifold approximation using union of tangent patches,” in Proc. 2nd IEEE Global Conf. Signal and Information Processing (GlobalSIP’14), Symposium on Information Processing for Big Data, Atlanta, GA, Dec. 3-5, 2014, pp. 458-462. [BibTeX]

[C48] A. Harms, W.U. Bajwa, and R. Calderbank, “Efficient linear time-varying system identification using chirp waveforms,” in Proc. 48th Asilomar Conf. Signals, Systems, and Computers, Pacific Grove, CA, Nov. 2-5, 2014, pp. 854-858. [BibTeX]

[C47] M. Tavan, R.D. Yates, and W.U. Bajwa, “Information in tweets: Analysis of a bufferless timing channel model,” in Proc. IEEE Intl. Symp. Information Theory (ISIT’14), Honolulu, HI, Jun. 29-Jul. 4, 2014, pp. 826-830. [BibTeX]

[C46] T. Ahmed and W.U. Bajwa, “A greedy, adaptive approach to learning geometry of nonlinear manifolds,” in Proc. IEEE Workshop Statistical Signal Processing (SSP’14), Gold Coast, Australia, Jun. 29-Jul. 2, 2014, pp. 133-136. [BibTeX]

[C45] T. Wu and W.U. Bajwa, “Subspace detection in a kernel space: The missing data case,” in Proc. IEEE Workshop Statistical Signal Processing (SSP’14), Gold Coast, Australia, Jun. 29-Jul. 2, 2014, pp. 93-96. [BibTeX]

[C44] T. Wu and W.U. Bajwa, “Revisiting robustness of the union-of-subspaces model for data-adaptive learning of nonlinear signal models,” in Proc. IEEE Intl. Conf. Acoustics, Speech, and Signal Processing (ICASSP’14), Florence, Italy, May 4-9, 2014, pp. 3390-3394. [BibTeX]

[C43] W.U. Bajwa, M.F. Duarte, and R. Calderbank, “Average case analysis of high-dimensional block-sparse recovery and regression for arbitrary designs,” in Proc. 17th Intl. Conf. Artificial Intelligence and Statistics (AISTATS’14), Reykjavik, Iceland, Apr. 22-25, 2014, pp. 57-67 (Acceptance rate: 120/335). [BibTeX]

[C42] M. Tavan, R.D. Yates, and W.U. Bajwa, “Capacity analysis of a discrete-time bufferless timing channel,” in Proc. 48th Annu. Conf. Information Sciences and Systems (CISS’14), Princeton, NJ, Mar. 19-21, 2014, pp. 1-6. [BibTeX]

[C41] A. Harms, W.U. Bajwa, and R. Calderbank, “Resource-efficient parametric recovery of linear time-varying systems,” in Proc. 5th IEEE Intl. Workshop Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP’13), Saint Martin, Dec. 15-18, 2013, pp. 200-203. [BibTeX]

[C40] A. Harms, W.U. Bajwa, and R. Calderbank, “Shaping the power spectra of bipolar sequences with application to sub-Nyquist sampling,” in Proc. 5th IEEE Intl. Workshop Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP’13), Saint Martin, Dec. 15-18, 2013, pp. 236-239. [BibTeX]

[C39] M. Nokleby and W.U. Bajwa, “Resource tradeoffs in distributed subspace tracking over the wireless medium,” in Proc. 1st IEEE Global Conf. Signal and Information Processing (GlobalSIP’13), Symposium on Network Theory, Austin, TX, Dec. 2013, pp. 823-826. [BibTeX]

[C38] M. Tavan, R.D. Yates, and W.U. Bajwa, “Bits through bufferless queues,” in Proc. 51st Annu. Allerton Conf. Communication, Control, and Computing, Monticello, IL, Oct. 2-4, 2013, pp. 755-762. [BibTeX]

[C37] H. Raja and W.U. Bajwa, “Cloud K-SVD: Computing data-adaptive representations in the cloud,” in Proc. 51st Annu. Allerton Conf. Communication, Control, and Computing, Monticello, IL, Oct. 2-4, 2013, pp. pp. 1474-1481. [BibTeX]

[C36] S. Sun, A.P. Petropulu, and W.U. Bajwa, “High-resolution networked MIMO radar based on sub-Nyquist observations,” in Proc. Workshop Signal Processing with Adaptive Sparse Structured Representations (SPARS’13), Lausanne, Switzerland, July 8-11, 2013. [BibTeX]

[C35] S. Sun, A.P. Petropulu, and W.U. Bajwa, “Target estimation in colocated MIMO radar via matrix completion,” in Proc. IEEE Intl. Conf. Acoustics, Speech, and Signal Processing (ICASSP’13), Vancouver, Canada, May 26-31, 2013, pp. 4144-4148. [BibTeX]

[C34] M. Nokleby, W.U. Bajwa, R. Calderbank, and B. Aazhang, “Toward resource-optimal averaging consensus over the wireless medium,” in Proc. 46th Asilomar Conf. Signals, Systems, and Computers, Pacific Grove, CA, Nov. 4-7, 2012, pp. 1197-1201. [BibTeX]

[C33] A. Harms, W.U. Bajwa, and R. Calderbank, “Rapid sensing of underutilized, wideband spectrum using the random demodulator,” in Proc. 46th Asilomar Conf. Signals, Systems, and Computers, Pacific Grove, CA, Nov. 4-7, 2012, pp. 1940-1944. [BibTeX]

[C32] W.U. Bajwa and D.G. Mixon, “Group model selection using marginal correlations: The good, the bad and the ugly,” in Proc. 50th Annu. Allerton Conf. Communication, Control, and Computing, Monticello, IL, Oct. 1-5, 2012, pp. 494-501. [BibTeX]

[C31] W.U. Bajwa, “Geometry of random Toeplitz-block sensing matrices: Bounds and implications for sparse signal processing,” in Proc. SPIE Defense, Security, and Sensing Conf. Compressive Sensing, Baltimore, MD, Apr. 23-27, 2012, pp. 1-7. [BibTeX]

[C30] M. Nokleby, W.U. Bajwa, R. Calderbank, and B. Aazhang, “Hierarchical averaging over wireless networks,” in Proc. IEEE Intl. Conf. Acoustics, Speech, and Signal Processing (ICASSP’12), Kyoto, Japan, Mar. 25-30, 2012, pp. 3121-3124. [Erratum] [BibTeX]

[C29] A. Harms, W.U. Bajwa, and R. Calderbank, “Faster than Nyquist, slower than Tropp,” in Proc. 4th IEEE Intl. Workshop Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP’11), San Juan, Puerto Rico, Dec. 13-16, 2011, pp. 345-348. [BibTeX]

[C28] M. Nokleby, W.U. Bajwa, R. Calderbank, and B. Aazhang, “Gossiping in groups: Distributed averaging over the wireless medium,” in Proc. 49th Annu. Allerton Conf. Communication, Control, and Computing, Monticello, IL, Sep. 28-30, 2011, pp. 1242-1249. [BibTeX]

[C27] L. Applebaum, W.U. Bajwa, R. Calderbank, and S. Howard, “Choir codes: Coding for full duplex interference management,” in Proc. 49th Annu. Allerton Conf. Communication, Control, and Computing, Monticello, IL, Sep. 28-30, 2011, pp. 1-8. [BibTeX]

[C26] D.G. Mixon, W.U. Bajwa, and R. Calderbank, “Frame coherence and sparse signal processing,” in Proc. IEEE Intl. Symp. Information Theory (ISIT’11), Saint-Petersburg, Russia, Jul. 31-Aug. 5, 2011, pp. 663-667. [BibTeX]

[C25] L. Applebaum, W.U. Bajwa, R. Calderbank, J. Haupt, and R. Nowak, “Deterministic pilot sequences for sparse channel estimation in OFDM systems,” in Proc. 17th IEEE Intl. Conf. Digital Signal Processing (DSP’11), Corfu, Greece, Jul. 6-8, 2011. [BibTeX]

[C24] K. Krishnamurthy, W.U. Bajwa, R. Willett, and R. Calderbank, “Fast level set estimation from projection measurements,” in Proc. IEEE Workshop Statistical Signal Processing (SSP’11), Nice, France, Jun. 28-30, 2011, pp. 585-588. [BibTeX]

[C23] M.F. Duarte, W.U. Bajwa, and R. Calderbank, “Regression performance of group lasso for arbitrary design matrices,” in Proc. Intl. Conf. Sampling Theory and Applications (SampTA’11), Singapore, May 2-6, 2011. [BibTeX]

[C22] W.U. Bajwa, K. Gedalyahu, and Y.C. Eldar, “On the identification of parametric underspread linear systems,” in Proc. IEEE Intl. Conf. Acoustics, Speech, and Signal Processing (ICASSP’11), Prague, Czech Republic, May 22-27, 2011, pp. 4088-4091. [BibTeX]

[C21] A. Harms, W.U. Bajwa, and R. Calderbank, “Beating Nyquist through correlations: A constrained random demodulator for sampling of sparse bandlimited signals,” in Proc. IEEE Intl. Conf. Acoustics, Speech, and Signal Processing (ICASSP’11), Prague, Czech Republic, May 22-27, 2011, pp. 5968-5971. [BibTeX]

[C20] L. Balzano, R. Nowak, and W.U. Bajwa, “Column subset selection with missing data,” in Proc. NIPS Workshop on Low-rank Methods for Large-scale Machine Learning, Whistler, Canada, Dec. 11, 2010. [BibTeX]

[C19] W.U. Bajwa, R. Calderbank, and S. Jafarpour, “Revisiting model selection and recovery of sparse signals using one-step thresholding,” in Proc. 48th Annu. Allerton Conf. Communication, Control, and Computing, Monticello, IL, Sep. 29-Oct. 01, 2010, pp. 977-984. [BibTeX]

[C18] L. Applebaum, W.U. Bajwa, M.F. Duarte, and R. Calderbank, “Multiuser detection in asynchronous on–off random access channels using lasso,” in Proc. 48th Annu. Allerton Conf. Communication, Control, and Computing, Monticello, IL, Sep. 29-Oct. 01, 2010, pp. 130-137. [BibTeX]

[C17] W.U. Bajwa, R. Calderbank, and S. Jafarpour, “Model selection: Two fundamental measures of coherence and their algorithmic significance,” in Proc. IEEE Intl. Symp. Information Theory (ISIT’10), Austin, TX, Jun. 13-18, 2010, pp. 1568-1572. [BibTeX]

[C16] W.U. Bajwa, A.M. Sayeed, and R. Nowak, “A restricted isometry property for structurally-subsampled unitary matrices,” in Proc. 47th Annu. Allerton Conf. Communication, Control, and Computing, Monticello, IL, Sep. 30-Oct. 02, 2009, pp. 1005-1012. [BibTeX]

[C15] W.U. Bajwa, A.M. Sayeed, and R. Nowak, “Sparse multipath channels: Modeling and estimation,” in Proc. 13th IEEE Digital Signal Processing Workshop, Marco Island, FL, Jan. 4-7, 2009, pp. 320-325. [BibTeX]

[C14] W.U. Bajwa, A.M. Sayeed, and R. Nowak, “Compressed sensing of wireless channels in time, frequency, and space,” in Proc. 42nd Asilomar Conf. Signals, Systems, and Computers, Pacific Grove, CA, Oct. 26-29, 2008, pp. 2048-2052. [Errata] [BibTeX]

[C13] W.U. Bajwa, A.M. Sayeed, and R. Nowak, “Learning sparse doubly-selective channels,” in Proc. 46th Annu. Allerton Conf. Communication, Control, and Computing, Monticello, IL, Sep. 23-26, 2008, pp. 575-582. (Extended Version: UW-Madison Tech. Report ECE-08-02, Jun. 2008) [BibTeX]

[C12] W.U. Bajwa, J. Haupt, G. Raz, and R. Nowak, “Compressed channel sensing,” in Proc. 42nd Annu. Conf. Information Sciences and Systems (CISS’08), Princeton, NJ, Mar. 19-21, 2008, pp. 5-10. [BibTeX]

[C11] J.D. Wierer, W.U. Bajwa, N. Boston, and R. Nowak, “Characterizing decoding robustness under parametric channel uncertainty,” in Proc. 45th Annu. Allerton Conf. Communication, Control, and Computing, Monticello, IL, Sep. 26-28, 2007, pp. 935-939. [BibTeX]

[C10] W.U. Bajwa, J. Haupt, G. Raz, S.J. Wright, and R. Nowak, “Toeplitz-structured compressed sensing matrices,” in Proc. 14th IEEE/SP Workshop Statistical Signal Processing (SSP’07), Madison, WI, Aug. 26-29, 2007, pp. 294-298 (Acceptance rate: 185/262). [BibTeX]

[C9] W.U. Bajwa, J. Haupt, A.M. Sayeed, and R. Nowak, “A universal matched source-channel communication scheme for wireless sensor ensembles,” in Proc. IEEE Intl. Conf. Acoustics, Speech, and Signal Processing (ICASSP’06), Toulouse, France, May 14-19, 2006, vol. 5, pp. 1153-1156. [BibTeX]

[C8] W.U. Bajwa, J. Haupt, A.M. Sayeed, and R. Nowak, “Compressive wireless sensing,” in Proc. 5th ACM/IEEE Intl. Conf. Information Processing in Sensor Networks (IPSN’06), Nashville, TN, Apr. 19-21, 2006, pp. 134-142 (Acceptance rate: 41/165). [BibTeX]

[C7] W.U. Bajwa, A.M. Sayeed, and R. Nowak, “Matched source-channel communication for field estimation in wireless sensor networks,” in Proc. 4th ACM/IEEE Intl. Conf. Information Processing in Sensor Networks (IPSN’05), Los Angeles, CA, Apr. 25-27, 2005, pp. 332-339 (Acceptance rate: 44/213). [BibTeX]

[C6] W.U. Bajwa, A.M. Sayeed, and R. Nowak, “Efficient communication strategies for distributed signal field estimation,” in Proc. 38th Asilomar Conf. Signals, Systems, and Computers, Pacific Grove, CA, Nov. 7-10, 2004, pp. 1371-1375. [BibTeX]

[C5] W.U. Bajwa, S.A. Ahmed, A. Abbas, S. Zulfiqar, and A. Qayyum, “Mobile IP based mobility management for 3G wireless networks,” in Proc. Intl. Symp. Wireless Systems and Networks (ISWSN’03), Dhahran, Saudi Arabia, Mar. 24-26, 2003.

[C4] W.U. Bajwa, S.A. Ahmed, A. Abbas, and H.A. Qadeer, “Modeling of processor delay and overall reduction in network latencies for real time, interactive applications,” in Proc. IEEE Students Conf. (ISCON’02), Lahore, Pakistan, Aug. 16-17, 2002, vol. 1, pp. 76-79.

[C3] W.U. Bajwa, S.A. Ahmed, A. Abbas, and H.A. Qadeer, “A novel design of a generational garbage collector,” in Proc. IEEE Students Conf. (ISCON’02), Lahore, Pakistan, Aug. 16-17, 2002, vol. 1, pp. 85-88.

[C2] A. Abbas, A. Ahmed, S.A. Ahmed, W.U. Bajwa, A. Anwar, and S. Abbasi, “A retargetable tool-suite for the design of application specific instruction set processors using a machine description language,” in Proc. IEEE Intl. Symp. Circuits and Systems (ISCAS’02), Scottsdale, AZ, May 26-29, 2002, vol. 1, pp. 425-428.

[C1] W.U. Bajwa, H.A. Qadeer, and M. Farooq, “Object-oriented design of a cycle accurate re-configurable simulator toolkit for DSP processors,” in Proc. IEEE Intl. Multi-Topic Conf. (INMIC’01), Lahore, Pakistan, Dec. 28-30, 2001, pp. 10-15.

[P3] A.O. Alabbasi, R. Hamila, W.U. Bajwa, and N. Al-Dhahir, “Method and apparatus for implementing sparse finite-impulse-response equalizers,” US Patent 10,382,101, Aug. 13, 2019.

[P2] M. Awadin, R. Hamila, N. Al-Dhahir, and W.U. Bajwa, “Method of identifying faulty antenna elements in massive uniform linear antenna arrays,” US Patent 10,135,551, Nov. 20, 2018.

[B1] W.U. Bajwa and A. Pezeshki, “Finite frames for sparse signal processing,” in Finite Frames, P. Casazza and G. Kutyniok, Eds. Cambridge, MA: Birkhäuser Boston, 2012, Ch. 10, pp. 303-335. [BibTeX]

[P1] W.U. Bajwa, A. Sayeed, R. Nowak, and J. Haupt, “Determining channel coefficients in a multipath channel,” US Patent 8,320,489, Nov. 27, 2012.

[T5] M.F. Duarte, W.U. Bajwa, and R. Calderbank, “The performance of group lasso for linear regression of grouped variables,” Technical Report TR-2010-10, Department of Computer Science, Duke University, Durham, NC, Feb. 2011. (Superseded by [J16]) [BibTeX]

[T4] W.U. Bajwa, R. Calderbank, and M.F. Duarte, “On the conditioning of random block subdictionaries,” Technical Report TR-2010-06, Department of Computer Science, Duke University, Durham, NC, Sep. 2010. (Superseded by [J16]) [BibTeX]

[T3] W.U. Bajwa, “New information processing theory and methods for exploiting sparsity in wireless systems,” Ph.D. Dissertation, University of Wisconsin-Madison, Madison, WI, 2009. [BibTeX]

[T2] W.U. Bajwa, A.M. Sayeed, and R. Nowak, “Learning sparse doubly-selective channels,” Technical Report ECE-08-02, University of Wisconsin-Madison, Madison, WI, Jun. 2008. [BibTeX]

[T1] W.U. Bajwa, “Joint source–channel communication for distributed estimation in wireless sensor networks,” M.S. Thesis, University of Wisconsin-Madison, Madison, WI, 2005.

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This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author’s copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.

COPYRIGHT NOTICE

This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author’s copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.