Jarvis Haupt  —  Publications

Submitted Manuscripts

• X. Li and J. Haupt, “Robust low-complexity randomized methods for locating outliers in large matrices,” submitted December 2016. (Arxiv)

• X. Li, T. Zhao, R. Arora, H. Liu, and J. Haupt, “Nonconvex sparse learning via stochastic optimization with progressive variance reduction,” submitted November 2016. (Arxiv)

• A. V. Sambasivan and J. Haupt, “Minimax lower bounds for noisy matrix completion under sparse factor models,” submitted September 2015. (Arxiv)

Journal Papers

• S. Jain, U. Oswal, K. S. Xu, B. Eriksson, and J. Haupt, “A compressed sensing decomposition of electro-dermal activity signals,” IEEE Transactions on Biomedical Engineering, 2016. (Arxiv)

• J. Druce, S. Gonella, M. Kadkhodaie, S. Jain, J.D. Haupt, “Locating material defects via wavefield demixing with morphologically germane dictionaries,” Structural Health Monitoring (SHM), 2016.

• A. Soni, S. Jain, J. Haupt, and S. Gonella, “Noisy matrix completion under sparse factor models,” IEEE Transactions on Information Theory, vol. 62, no. 6, pp. 3636-3661, June 2016. (Arxiv)

• J. Druce, J. Haupt, and S. Gonella, “Anomaly-sensitive dictionary learning for structural diagnostics from ultrasonic wavefields,” IEEE Trans. Ultrasonics, Ferroelectrics, and Frequency Control, vol. 62, no. 7, pp. 1384-1396, July 2015.

• X. Li and J. Haupt, “Identifying outliers in large matrices via randomized adaptive compressive sampling,” IEEE Transactions on Signal Processing, vol. 63, no. 7, pp. 1792-1807, March-April 2015. (Arxiv)

• A. Soni and J. Haupt, “On the fundamental limits of recovering tree sparse vectors from noisy linear measurements,” IEEE Transactions on Information Theory, vol. 60, no. 1, pp. 133-149, January 2014. (Arxiv)

• S. Gonella and J. Haupt, “Automated defect localization via low rank plus outlier modeling of propagating wavefield data,” IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, vol. 60, no. 12, pp. 2553-2565, December 2013. (Arxiv)

• J. Haupt, R. Castro, and R. Nowak, “Distilled sensing: Adaptive sampling for sparse detection and estimation,” IEEE Transactions on Information Theory, vol. 57, no. 9, pp. 6222-6235, September 2011. (PDF)

• J. Haupt, W.U. Bajwa, G. Raz, and R. Nowak, “Toeplitz compressed sensing matrices with applications to sparse channel estimation,” IEEE Transactions on Information Theory, vol. 56, no. 11, pp. 5862-5875, November 2010. (PDF)

• W.U. Bajwa, J. Haupt, A.M. Sayeed, and R. Nowak, “Compressed channel sensing: A new approach to estimating sparse multipath channels,” Proceedings of the IEEE, vol. 98, no. 6, pp. 1058-1076, July 2010. (PDF)

• J. Haupt, W.U. Bajwa, M. Rabbat, and R. Nowak, “Compressed sensing for networked data,” IEEE Signal Processing Magazine - Special Issue on Compressive Sensing, vol. 25, no. 2, pp. 92-101, March 2008. (PDF)

• W.U. Bajwa, J. Haupt, A.M. Sayeed, and R. Nowak, “Joint source-channel communication for distributed estimation in sensor networks,” IEEE Transactions on Information Theory - Special Issue on Relaying and Cooperation in Communication Networks, vol. 53, no. 10, pp. 3629-3653, October 2007. (PDF)

• J. Haupt and R. Nowak, “Signal reconstruction from noisy random projections,” IEEE Transactions on Information Theory, vol. 52, no. 9, pp. 4036-4048, September 2006. (PDF)

Book Chapters

• J. Haupt and R. Nowak, “Adaptive sensing for sparse recovery,” in Compressed Sensing: Theory and Applications, Y. Eldar and G. Kutyniok eds., Cambridge University Press, 2012. (PDF)

Conference Papers

• M. K. Elyaderani, S. Jain, J. Druce, S. Gonella, and J. Haupt, “Group-level support recovery guarantees for group lasso estimator,” IEEE International Conference on Acoustics, Speech, and Signal Processing, 2017 (Accepted, to appear).

• S. Jain and J. Haupt, “On convolutional approximations to linear dimensionality reduction operators for large scale data processing,” Proc. IEEE International Conference on Acoustics, Speech, and Signal Processing, 2017 (Accepted, to appear).

• S. Rambhatla, X. Li and J. Haupt, “A dictionary based generalization of robust PCA,” Proc. IEEE Global Conference on Signal and Information Processing, December 2016.

• J. Ren, X. Li and J. Haupt, “Robust PCA via tensor outlier pursuit,” Proc. Asilomar Conference on Signals, Systems, and Computers, November 2016.

• J. Druce, S. Gonella, M. Kadkhodaie, S. Jain, and J. Haupt, “Defect triangulation via demixing algorithms based on dictionaries with different morphological complexity,” Proc. 8th European Workshop On Structural Health Monitoring, July 2016.

• X. Li, T. Zhao, R. Arora, H. Liu, and J. Haupt, "Stochastic variance reduced pptimization for nonconvex sparse learning,’’ JMLR Workshop and Conference Proceedings, Vol. 48: Proceedings of the 33rd Intl. Conference on Machine Learning, June 2016.

• X. Li and J. Haupt, “A refined analysis for the sample complexity of adaptive compressive outlier sensing,” IEEE Workshop on Statistical Signal Processing, June 2016.

• M. Kadkhodaie, S. Jain, J. Haupt, J. Druce, and S. Gonella, “Locating rare and weak material anomalies by convex demixing of propagating wavefields,” Proc. IEEE Workshop on Computational Advances in Multi-Sensor Adaptive Processing, pp. 373-376, December 2015.

• X. Li and J. Haupt, “Locating salient group-structured image features via adaptive compressive sensing,” Proc. IEEE Global Conference on Signal and Information Processing, December 2015. (** Best Student Paper Award Winner! **)

• J. Druce, M. Kadkhodaie, J. Haupt and S. Gonella, “Structural diagnostics via anomaly-driven demixing of wavefield data," International Workshop on Structural Health Monitoring, pp. 1236-1242, September 2015. (** Student Best Paper Award Winner! **)

• A. Weinstein, L. Fortson, T. Brantseg, C. Rulten, R. Lutz, J. Haupt, M. Kadkhodaie Elyaderani, and J. Quinn, “Testing a novel self-assembling data paradigm in the context of IACT data,” Proc. Intl. Cosmic Ray Conference, July 2015.

• A. Jang, A. Gutierrez, D. Xiao, C. A. Corum, V. Mandic, J. Haupt, and M. Garwood, “Reconstruction Strategies for Pure 2D Spatiotemporal MRI," Proc. International Society for Magnetic Resonance in Medicine Annual Mtg., June 2015.

• I. Bogunovic, V. Cevher, J. Haupt, and J. Scarlett, “Active learning of self- concordant like multi-index functions," Proc. IEEE International Conference on Acoustics, Speech, and Signal Processing, pp. 2189-2193, April 2015.

• X. Li and J. Haupt, “Outlier identification via randomized adaptive compressive sampling," Proc. IEEE International Conference on Acoustics, Speech, and Signal Processing, pp. 3302-3306, April 2015.

• A. Soni, S. Jain, J. Haupt, and S. Gonella, “Error bounds for maximum likelihood matrix completion under sparse factor models," Proc. IEEE Global Conference on Signal and Information Processing, pp. 399-403, December 2014.

• A. Soni and J. Haupt, “Estimation error guarantees for Poisson denoising with sparse and structured dictionary models,” Proc. IEEE International Symposium on Information Theory, pp. 2002-2006, June/July 2014. (PDF)

• J. D. Haupt, N. D. Sidiropoulos, and G. B. Giannakis, “Sparse dictionary learning from 1-bit data,” Proc. IEEE International Conference on Acoustics, Speech, and Signal Processing, pp. 7664-7668, May 2014. (PDF, Errata)

• A. Soni, J. Haupt, and F. Porikli, “Recycled linear classifiers for multiclass classification,” Proc. IEEE International Conference on Acoustics, Speech, and Signal Processing, pp. 2957-2961, May 2014. (PDF))

• J. Druce, J. D. Haupt, and S. Gonella, “Anomaly detection in heterogenous media via saliency analysis of propagating wavefields,” Proc. SPIE Conference on Health Monitoring of Structural and Biological Systems, March 2014.

• J. Haupt, “Locating salient items in large data collections with compressive linear measurements,” Proc. IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, pp. 9-12, December 2013. (PDF)

• A. Soni and J. Haupt, “Fundamental limits for support recovery of tree-sparse signals from noisy compressive samples,” Proc. IEEE Global Workshop on Signal and Information Processing, pp. 961-964, December 2013. (PDF)

• S. Rambhatla and J. Haupt, “Semi-blind source separation via sparse representations and online dictionary learning,” Proc. Asilomar Conference on Signals, Systems, and Computers, pp. 1687-1691, November 2013. (Arxiv)

• S. Jain, A. Soni, and J. Haupt, “Compressive measurement designs for estimating structured signals in structured clutter: A Bayesian experimental design approach,” Proc. Asilomar Conference on Signals, Systems, and Computers, pp. 163-167, November 2013. (Arxiv))

• S. Jain, A. Soni, J. Haupt, N. Rao, and R. Nowak, “Knowledge-enhanced compressive measurement designs for estimating sparse signals in clutter,” Signal Processing with Adaptive Structured Sparse Representations (SPARS) Workshop, July 2013. (Abstract, Extended Version)

• A. Soni and J. Haupt, “Level set estimation from compressive measurements using box constrained total variation regularization,” Proc. IEEE Conference on Image Processing, pp. 2573-2576, September-October 2012. (PDF))

• J. Haupt, R. Baraniuk, R. Castro, and R. Nowak, “Sequentially designed compressed sensing,” Proc. IEEE/SP Workshop on Statistical Signal Processing, pp. 401-404, August 2012. (PDF)

• A. Soni and J. Haupt, “Learning sparse representations for adaptive compressive sensing,” Proc. IEEE Conference on Acoustics, Speech, and Signal Processing, pp. 2097-2100, March 2012. (PDF)

• A. Soni and J. Haupt, “Efficient adaptive compressive sensing using sparse hierarchical learned dictionaries,” Proc. Asilomar Conference on Signals, Systems, and Computers, pp. 1250-1254, November 2011. (PDF)

• L. Applebaum, W.U. Bajwa, A.R. Calderbank, J. Haupt and R. Nowak, “Deterministic pilot sequences for sparse channel estimation in OFDM systems,” Proc. 17th International Conference on Digital Signal Processing, pp. 1-7, July 2011. (PDF)

• J. Haupt and R. Baraniuk, “Robust support recovery using sparse compressive sensing matrices,” Proc. 45th Annual Conf. on Information Sciences and Systems, pp. 1-6, Baltimore, MD, March 2011. (PDF)

• J. Haupt, R. Castro, and R. Nowak, “Improved bounds for sparse recovery from adaptive measurements,” Proc. IEEE International Symposium on Information Theory, pp. 1563-1567, Austin, TX, June 2010. (PDF)

• J. Haupt, L. Applebaum, and R. Nowak, “On the restricted isometry of deterministically subsampled Fourier matrices,” Proc. 44th Annual Conf. on Information Sciences and Systems, pp. 1-6, Princeton, NJ, March 2010. (PDF)

• J. Haupt, R. Baraniuk, R. Castro, and R. Nowak, “Compressive distilled sensing: Sparse recovery using adaptivity in compressive measurements,” Proc. 43rd Asilomar Conf. on Signals, Systems, and Computers, pp. 1551-1555, Pacific Grove, CA, November 2009. (PDF)

• J. Haupt, R. Castro, and R. Nowak, “Distilled sensing: Selective sampling for sparse signal recovery,” Proc. 12th International Conference on Artificial Intelligence and Statistics (AISTATS), pp. 216-223, Clearwater Beach, Florida, April 2009. (PDF)

• J. Haupt, R. Castro, and R. Nowak, “Adaptive sensing for sparse signal recovery,” Proc. IEEE Digital Signal Processing Workshop and Workshop on Signal Processing Education, pp. 702-707, Marco Island, FL, 2009, January 2009. (PDF)

• J. Haupt, R. Castro, and R. Nowak, “Adaptive discovery of sparse signals in noise,” Proc. 42nd Asilomar Conf. on Signals, Systems, and Computers, pp. 1727-1731, Pacific Grove, CA, October 2008. (PDF)

• G. Fudge, M. Chivers, S. Ravindran, R. Bland, P. Pace, and J. Haupt, “A Nyquist folding analog-to-information receiver,” Proc. 42nd Asilomar Conf. on Signals, Systems, and Computers, pp. 541-545, Pacific Grove, CA, October 2008. (.publicationsasilomar08_nyfr.pdf PDF])

• W.U. Bajwa, J. Haupt, G. Raz, and R. Nowak, “Compressed channel sensing,” Proc. 42nd Annual Conf. on Information Sciences and Systems, pp. 5-10, Princeton, NJ, March 2008. (PDF)

• R. Castro, J. Haupt, R. Nowak, and G. Raz “Finding needles in noisy haystacks,” Proc. IEEE Intl. Conf. on Acoustics, Speech and Signal Processing, pp. 5133-5136, Las Vegas, NV, April 2008. (PDF)

• W.U. Bajwa, J. Haupt, G. Raz, S.J. Wright, and R. Nowak, “Toeplitz structured compressed sensing matrices,” Proc. IEEE/SP 14th Workshop on Statistical Signal Processing, pp. 294-298, Madison, WI, August 2007. (PDF)

• F. Boyle, J. Haupt, G. Fudge, and A. Yeh, “Detecting signal structure from randomly-sampled data,” Proc. IEEE/SP 14th Workshop on Statistical Signal Processing, pp. 326-330, Madison, WI, August 2007. (PDF)

• J. Haupt and R. Nowak, “Compressive sampling for signal detection,” Proc. IEEE Intl. Conf. on Acoustics, Speech, and Signal Processing, vol. 3, pp. 1509-1512, Honolulu, HI, April 2007. (PDF)

• J. Haupt, R. Castro, R. Nowak, G. Fudge, and A. Yeh, “Compressive sampling for signal classification,” Proc. 40th Asilomar Conf. on Signals, Systems, and Computers, pp. 1430-1434, Pacific Grove, CA, October-November 2006. (PDF)

• J. Haupt and R. Nowak, “Compressive sampling vs. conventional imaging,” Proc. IEEE Intl. Conf. on Image Processing, pp. 1269-1272, Atlanta, GA, October 2006. (PDF)

• W.U. Bajwa, J. Haupt, A.M. Sayeed, and R. Nowak, “A universal matched source-channel communication scheme for wireless sensor ensembles,” Proc. IEEE Intl. Conf. on Acoustics, Speech, and Signal Processing, vol. 5, pp. 1153-1156, Toulouse, France, May 2006. (PDF)

• R. Castro, J. Haupt, and R. Nowak, “Compressed sensing vs. active learning,” Proc. IEEE Intl. Conf. on Acoustics, Speech, and Signal Processing, vol. 3, pp. 820-823, Toulouse, France, May 2006. (PDF)

• W.U. Bajwa, J. Haupt, A.M. Sayeed, and R. Nowak, “Compressive wireless sensing,” Proc. 5th Intl. Conf. on Information Processing in Sensor Networks, pp. 134-142, Nashville, TN, April 2006. (PDF)

• M. Rabbat, J. Haupt, A. Singh, and R. Nowak, “Decentralized compression and predistribution via randomized gossiping,” Proc. 5th Intl. Conf. on Information Processing in Sensor Networks, pp. 51-59, Nashville, TN, April 2006. (PDF)

• J. Haupt and R. Nowak, “Signal reconstruction from noisy random projections with applications to wireless sensing,” Proc. IEEE/SP 13th Workshop on Statistical Signal Processing, pp. 1182-1187, Bordeaux, France, July 2005. (PDF)

Patent Applications

• “System and method for reconstructing images from spatiotemporally-encoded magnetic resonance imaging data,” Albert Jang, Michael Garwood, Vuk Mandic, Jarvis Haupt, Di Xiao, Alexander Gutierrez, Naoharu Kobayashi, and Steen Moeller, May 2015 (provisional).

Patents

• “Method of adaptive data acquisition,” Rui M. Castro, Jarvis D. Haupt, and Robert D. Nowak, US Patent Number 8521473, issued August 27, 2013.

• “Determining channel coeffcients in a multipath channel,” Waheed U. Bajwa, Akbar M. Sayeed, Robert D. Nowak, and Jarvis Haupt, US Patent Number 8320489, issued November 27, 2012.

• “System and method of signal sensing, sampling, and processing through the exploitation of channel mismatch effects,” Gil M. Raz, Jerrrey H. Jackson, and Jarvis D. Haupt, US Patent Number 7994959, issued August 9, 2011.

Other Publications

• J. Haupt, “New theory and methods in adaptive and compressive sampling for sparse discovery,” Ph.D. Dissertation, University of Wisconsin – Madison, August 2009. (PDF)

• J. Haupt and R. Nowak, “A generalized restricted isometry property,” University of Wisconsin - Madison Technical Report ECE-07-1, May 2007. (PDF)