Publications

2017

G. Ongie, R. Willett, R. D. Nowak, and L. Balzano, “Algebraic Variety Models for High-Rank Matrix Completion.” arXiv:1703:09631, 2017.

K. J. Borkowski, S. P. Reynolds, D. A. Green, U. Hwang, R. Petre, K. Krishnamurthy, and R. Willett, “Asymmetric Expansion of the Youngest Galactic Supernova Remnant G1.9+0.3.” To appear in The Astrophysical Journal Letters, 2017.

Kwang-Sung Jun, Francesco Orabona, Rebecca Willett, Stephen Wright, “Improved Strongly Adaptive Online Learning using Coin Betting.” http://arxiv.org/abs/1610.04578, to appear in AISTATS 2017.

N. Rao, R. Ganti, L. Balzano, R. Willett, and R. Nowak, “On learning high-dimensional structured single index models.” arXiv:1603.03980, to appear in AAAI-17.

2016

P. Guan, M. Raginsky, R. Willett, and D.-S. Zois, “Regret Minimization Algorithms for Single-Controller Zero-Sum Stochastic Games.” 55th IEEE Conference on Decision and Control, 2016

X. Jiang and R. Willett, “Online Data Thinning via Multi-Subspace Tracking.” arXiv:1609.03544, 2016. Code.

E. Hall, G. Raskutti, and R. Willett, ”Inference of High-dimensional Autoregressive Generalized Linear Models.” arXiv:1605.02693, 2016.

A. Yankovich, C. Zhang, A. Oh, T. Slater, F. Azough, R. Freer, S. Haigh, R. Willett, P. Voyles, “Non-rigid registration and non-local principle component analysis to improve electron microscopy spectrum images,” Nanotechnology, vol. 27, no. 36, 2016.

E. Hall, G. Raskutti, and R. Willett, “Inference of High-dimensional Poisson Autoregressive Models.” IEEE Statistical Signal Processing Workshop, 2016.

X. Jiang, P. Reynaud-Bouret, V. Rivoirard, L. Sansonnet, and R. Willett,“Genomic Transcription Regulatory Element Location Analysis via Poisson weighted LASSO.” IEEE Statistical Signal Processing Workshop, 2016.

D. Pimentel-Alarcon, L. Balzano, R. Marcia, R. Nowak, and R. Willett, “Group-sparse subspace clustering with missing data.” IEEE Statistical Signal Processing Workshop, 2016.

W. Marais, R. Holz, Y. H. Hu, R. Kuehn, E. Eloranta, and R. Willett, “A New Approach To Inverting Backscatter and Scatter from Photon-Limited Lidar Observations.” To appear in Applied Optics, 2016.

J. Mueller, J. Gallagher, R. Chitalia, M. Krieger, A. Erkanli, R. Willett, J. Geradts, and N. Ramanujam, “Rapid staining and imaging of sub-nuclear features to differentiate between malignant and benign breast tissues at a point-of-care setting,” J. Cancer Res. Clin. Oncol. 142(7), 1475-1486, 2016.

W. Marais, R. Holz, Y. H. Yu, and R. Willett, “Atmospheric Lidar Imaging and Poisson Inverse Problems.” IEEE International Conference on Image Processing, 2016.

H. Fu, J. Mueller, M. Whitley, D. Cardona, R. Willett, D. Kirsch, Q. Brown, and N. Ramanujam, “Structured illumination microscopy and a quantitative image analysis for the detection of positive margins in a pre-clinical genetically engineered mouse model of sarcoma,” PLoS ONE, 2016.

2015

R. Ganti, L. Balzano, and R. Willett, “Matrix Completion Under Monotonic Single Index Models,” in Proc. Neural Information Processing Systems, 2015.

X. Jiang, P. Reynaud-Bouret, V. Rivoirard, L. Sansonnet, and R. Willett, “A data-dependent weighted lasso under poisson noise,” submitted. arXiv:1509.08892, 2015.

A. Oh and R. Willett, “Regularized non-Gaussian image denoising,” submitted. arXiv:1508.02971, 2015.

R. Ganti, N. Rao, R. Willett, and R. Nowak, “Learning single index models in high dimensions,” arXiv:1506.08910, 2015.

J. Mueller, H. Fu, J. Mito, M. Whitley, R. Chitalia, A. Erkanli, L. Dodd, D. Cardona, J. Geradts, R. Willett, D. Kirsch, and N. Ramanujam, “A quantitative microscopic approach to predict local recurrence based on in vivo intraoperative imaging of sarcoma tumor margins,” International Journal of Cancer, vol. 137, no. 10, pp. 2403–12, 2015.

E. Hall and R. Willett, “Online convex optimization in dynamic environments,” IEEE Journal of Selected Topics in Signal Processing – Signal Processing for Big Data, vol. 9, no. 4, arXiv:1307:5944, 2015. code

E. Hall and R. Willett, “Online learning of neural network structure from spike trains,” in Proceedings of the 7th International IEEE EMBS Neural Engineering Conference (NER’15), 2015. code

2014

R. Willett, “The dark side of image reconstruction: Emerging methods for photon-limited imaging,” SIAM News, Online version here, 2014.

E. Hall and R. Willett. “Tracking Dynamic Point Processes on Networks”, arXiv:1409.0031, 2013. code

T. Routtenberg, Y. Xie, R. Willett, and L. Tong, “PMU based detection of imbalance in three-phase power systems,” IEEE Transactions on Power Systems, vol. 30, no. 4, 2014. arXiv:1409.5530

K. J. Borkowski, S. P. Reynolds, D. A. Green, U. Hwang, R. Petre, K. Krishnamurthy, and R. Willett, “Nonuniform Expansion of the Youngest Galactic Supernova Remnant G1.9+0.3,” Accepted to Astrophysical Journal Letters, 2014. arXiv:1406.2287

P. Guan, M. Raginsky, and R. Willett. “Online Markov decision processes with Kullback-Leibler control cost.” IEEE Transactions on Automatic Control, vol. 59, no. 6, pp. 1423-1438, 2014. Preliminary version appeared in Proceedings of 2012 American Control Conference (Montreal, Quebec, Canada, June 2012)

J. M. Nichols, A. K. Oh, and R. Willett, “Reducing basis mismatch in harmonic signal recovery via alternating convex search,” Signal Processing Letters, vol. 21, no. 8, pp. 1007–1011, arXiv:1406.5231, 2014. Code here.

X. Jiang, G. Raskutti, and R. Willett, “Minimax Optimal Rates for Poisson Inverse Problems with Physical Constraints,” To appear in IEEE Transactions on Information Theory, arXiv:1403.6532, 2014.

J. Salmon, Z. Harmany, C. Deledalle, and R. Willett, “Poisson noise reduction with non-local PCA,” Journal of Mathematical Imaging and Vision, vol. 48, no. 2, pp. 279–294, arXiv:1206:0338, 2014.

A. Oh, Z. Harmany, and R. Willett, “To e or not to e in Poisson image reconstruction,” ICIP 2014. “Top 10% Paper”.

2013

A. Oh, Z. Harmany, and R. Willett, “Logarithmic total variation regularization for cross-validation in photon-limited imaging,” in IEEE International Conference on Image Processing (ICIP), 2013.

R. Willett, M. F. Duarte, M. A. Davenport, and R. G. Baraniuk, “Sparsity and structure in hyperspectral imaging: Sensing, reconstruction, and target detection,” to appear in IEEE Signal Processing Magazine, 2013.

P. Guan, M. Raginsky, and R. Willett, “Relax but stay in control: From value to algorithms for online Markov decision processes,” submitted, arXiv:1310.7300, 2013.

E. Hall and R. Willett. “Online optimization in dynamic environments,” arXiv:1307:5944, 2013.

Y. Xie and R. Willett. “Online logistic regression on manifolds,” IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2013.

K. Krishnamurthy, W. Bajwa, and R. Willett. “Level set estimation from projection measurements: Performance guarantees and fast computation.” SIAM Journal on Imaging Sciences, vol. 6, no. 4, pp. 2047–2074 arXiv:1209.3990, 2013.

Y. Xie, J. Huang, and R. Willett. “Changepoint detection for high-dimensional time series with missing data.” In IEEE Journal of Selected Topics in Signal Processing, vol. 7, no. 1, 2013. arXiv:1208:5062.

K. J. Borkowski, S. P. Reynolds, U. Hwang, D. A. Green, R. Petre, K. Krishnamurthy, and R. Willett. “Supernova ejecta in the youngest galactic supernova remnant G1.9+0.3,” Astrophysical Journal Letters, 771(1), 2013.

J. L. Mueller, Z. T. Harmany, J. K. Mito, S. A. Kennedy, Y. Kim, L. Dodd, J. Geradts, D. G. Kirsch, R. M. Willett, J. Q. Brown, and N. Ramanujam. “Quantitative segmentation of fluorescence microscopy images of heterogeneous tissue: Application to the detection of residual disease in tumor margins,” PLoS ONE 2013.

E. Hall and R. Willett. “Foreground and background reconstruction in Poisson video,” ICIP 2013.

A. K. Oh, Z. T. Harmany, and R. Willett. “Logarithmic total variation regularization for cross-validation in photon-limited imaging,” ICIP 2013.

E. Hall and R. Willett. “Dynamical Models and Tracking Regret in Online Convex Programming,” ICML 2013, arXiv:1301.1254, 2013.

M. Raginsky, J. Silva, S. Lazebnik, and R. Willett. “A recursive procedure for density estimation on the binary hypercube” Electron. J. Statist., vol. 7, 820-858, 2013. arXiv:1112.1450.

2012

E. Arias-Castro, J. Salmon, and R. Willett. “Oracle inequalities and minimax rates for non-local means and related adaptive kernel-based methods.” Accepted to SIAM Journal on Imaging Sciences, 2012. arXiv:1112:4434. (Code.)

K. Krishnamurthy, R. Willett, and M. Raginsky. “Target Detection Performance Bounds in Compressive Imaging.” Accepted for publication in EURASIP Journal on Advances in Signal Processing. arXiv:1112.0504.

Z. Harmany, X. Jiang, and R. Willett. “The Value of Multispectral Observations in Photon-Limited Quantitative Tissue Analysis.” Statistical Signal Processing Workshop (SSP), 2012.

J. Salmon, R. Willett, and E. Arias-Castro. “A Two-Stage Denoising Filter: The Preprocessed Yaroslavsky Filter.” Statistical Signal Processing Workshop (SSP), 2012. arXiv:1208:6516. (Code.)

J. Salmon, C.-A. Deledalle, R. Willett, and Z. Harmany. “Poisson Noise Reduction with Non-Local PCA.” ICASSP 2012. (Code.)

Z. Harmany, R. Marcia, and R. Willett. “This is SPIRAL-TAP: Sparse Poisson Intensity Reconstruction ALgorithms – Theory and Practice.” IEEE Transactions on Signal Processing, vol. 21(3), 2012. arXiv:1005.4274.

2011

Z. Harmany, R. Marcia, and R. Willett. “Spatio-temporal Compressed Sensing with Coded Apertures and Keyed Exposures.” Submitted, 2011. arXiv:1111.7247.

R. Willett and M. Raginsky. “Poisson Compressed Sensing.” Defense Applications of Signal Processing 2011.

M. Raginsky, S. Jafarpour, Z. Harmany, R. Marcia, R. Willett, and R. Calderbank. “Performance bounds for expander-based compressed sensing in Poisson noise.” IEEE Transactions on Signal Processing, vol. 59, no. 9, 2011.

R. Willett, R. Marcia, and J. Nichols. “Compressed sensing for practical optical systems: a tutorial,” Optical Engineering, vol. 50, no. 7, pp. 072601 1-13, 2011. http://dx.doi.org/10.1117/1.3596602.

K. Krishnamurthy, W. U. Bajwa, R. Willett, and R. Calderbank. “Fast level set estimation from projection measurements.” Statistical Signal Processing Workshop 2011.

E. Wang, J. Silva, R. Willett, L. Carin. “Dynamic Relational Topic Model for Social Network Analysis with Noisy Links.” Statistical Signal Processing Workshop 2011.

M. Raginsky, N. Kiarashi, and R. Willett. “Decentralized online convex programming with local information.” Proceedings of American Control Conference, 2011.

R. Willett. “Errata: Sampling Trajectories for Sparse Image Recovery.” 2011. Pertains to:

  • “Short and Smooth Sampling Trajectories for Compressed Sensing”, ICASSP 2011.
  • “Smooth Sampling Trajectories for Sparse Recovery in MRI”, ISBI 2011.
  • “Sampling Trajectories for Sparse Image Recovery”, SAMPTA 2011.

E. Wang, J. Silva, R. Willett, and L. Carin. “Time-Evolving Modeling of Social Networks,” ICASSP 2011.

C. Horn and R. Willett. “Online anomaly detection with expert system feedback in social networks,” ICASSP 2011.

2010

K. J. Borkowski, S. P. Reynolds, D. A. Green, U. Hwang, R. Petre, K. Krishnamurthy, and R. Willett. “Radioactive Scandium in the Youngest Galactic Supernova Remnant G1.9+0.3,” The Astrophysical Journal Letters, 2010. arXiv:1006.3552.

M. Raginsky, R. Willett, C. Horn, J. Silva, R. Marcia. “Sequential anomaly detection in the presence of noise and limited feedback.” IEEE Transactions on Information Theory, vol. 58(8), 5544-5562, 2010.

K. Krishnamurthy, M. Raginsky, and R. Willett. “Multiscale photon-limited hyperspectral image reconstruction,” SIAM Journal on Imaging Sciences, Volume 3, Issue 3, pp 619-645, 2010.

M. Raginsky, R. Willett, Z. Harmany, and R. Marcia. “Compressed sensing performance bounds under Poisson noise,” IEEE Transactions on Signal Processing Volume 58, Issue 8, pp 3990-4002, 2010.

R. Marcia, R. Willett, and Z. Harmany. “Compressive Optical Imaging: Architectures and Algorithms”, Optical and Digital Image Processing Fundamentals and Applications, edited by G. Cristobal, P. Schelkens and H. Thienpont, 2010. Accepted for publication.

M. Raginsky, S. Jafarpour, R. Willett and R. Calderbank. “Fishing in Poisson streams: focusing on the whales, ignoring the minnows.” Proc. of the Forty-Fourth Conference on Information Sciences and Systems (Asilomar), arXiv:1003.28362010. Winner of best student paper award.

Z. Harmany, D. Thompson, R. Willett, and R. Marcia. “Gradient projection for linearly constrained convex optimization in sparse signal recovery,” IEEE International Conference on Image Processing, 2010.

K. Krishnamurthy, M. Raginsky, and R. Willett. “Hyperspectral target detection from incoherent projections,” 35th International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2010.

2009

S. Jafarpour, R. Willett, M. Raginsky and R. Calderbank. “Performance Bounds for Expander-Based Compressed Sensing in the Presence of Poisson Noise,” Forty-Third Asilomar Conference on Signals, Systems and Computers, 2009. Winner of best student paper award.

Z. Harmany, R. Marcia and R. Willett. “Sparse Poisson Intensity Reconstruction Algorithms,” Proc. IEEE Workshop on Statistical Signal Processing, 2009.

M. Raginsky and R. Willett. “Sequential anomaly detection in the presence of noise and limited feedback,” Duke University Technical Report ECE-2009-01.

G. Ybarra, L. M. Collins, L. G. Huettel, H. Z. Massoud, J. Board, M. Brooke, N. Jokerst, R. Roy Choudhury, M. R. Gustafson, R. M. Willett and K. Coonley. “Integrating sensing and processing in an electrical and computer engineering curriculum,” Frontiers in Education Conference, 2009.

H. Jared Doot, Kevin Eliceiri, Robert Nowak and Rebecca Willett. “Image Reconstruction of Multiphoton Microscopy Data”, IEEE International Symposium on Biomedical Imaging, 2009.

Clayton Scott, Gowtham Bellala, and Rebecca Willett. “The False Discovery Rate for Statistical Pattern Recognition,” Electronic Journal of Statistics, vol. 3, pp 651-677, 2009.

Rebecca Willett and Maxim Raginsky. “Performance bounds on compressed sensing with Poisson noise,” IEEE International Symposium on Information Theory, 2009.

Maxim Raginsky, Roummel Marcia, Jorge Silva and Rebecca Willett. “Sequential probability assignment via online convex programming using exponential families,” IEEE International Symposium on Information Theory, 2009

Roummel Marcia, Zachary Harmany, and Rebecca Willett. “Compressive Coded Aperture Imaging,” SPIE Electronic Imaging, 2009.

Jorge Silva and Rebecca Willett. “Hypergraph-based detection of anomalous high-dimensional co-occurrences ,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol 31, no. 3, pp 563-569, 2009.

2008

Maxim Raginsky, Svetlana Lazebnik, Rebecca Willett, and Jorge Silva. “Near-Minimax Recursive Density Estimation on the Binary Hypercube,” NIPS 2008.

Roummel Marcia, Changsoon Kim, Jungsang Kim, David Brady, and Rebecca Willett. “Superimposed video disambiguation for increased field of view“, Optics Express, vol 16, no. 31, 16352-16363.

Scott McCain, Rebecca Willett, and David Brady. “Multi-excitation Raman spectroscopy technique for fluorescence rejection“, Optics Express, vol 16, no. 15, pp 10975-10991.

Zachary Harmany, Rebecca Willett, Aarti Singh, and Robert Nowak. “Controlling the error in fMRI: Hypothesis testing or set estimation?“, IEEE International Symposium on Biomedical Imaging — ISBI 2008.

Roummel Marcia and Rebecca Willett. “Compressive Coded Aperture Video Reconstruction“, European Signal Processing Conference — EUSIPCO 2008.

Jorge Silva and Rebecca Willett. “Detection of anomalous meetings in a social network,” Proc. Conference on Information Sciences and Systems — CISS 2008.

Roummel Marcia and Rebecca Willett. “Compressive Coded Aperture Superresolution Image Reconstruction,” Proc. IEEE Int. Conf. Acoust., Speech, Signal Processing — ICASSP 2008.

Mohan Shankar, Rebecca Willett, Nikos Pitsianis, Timothy Schulz, Robert Gibbons, Robert Te Kolste, J. Carriere, C. Chen, D. Prather, David Brady. “Thin infrared imaging systems through multi-channel sampling,” Applied Optics, vol. 47, no. 10, pp. B1-B10, 2008.

Ashwin Wagadarikar, Renu John, Rebecca Willett, and David Brady, “Single disperser design for coded aperture snapshot spectral imaging,” Applied Optics, vol. 47, no. 10, pp. B44-B51, 2008.

2007

Rebecca Willett and Robert Nowak. “Minimax Optimal Level Set Estimation, IEEE Transactions on Image Processing, vol. 16, no. 12, pp. 2965-2979, 2007.

Rebecca Willett and Robert Nowak, “Multiscale Poisson Intensity and Density EstimationIEEE Transactions on Information Theory, vol. 53, no. 9, pp. 3171-3187, 2007.

Clayton Scott, Gowtham Bellala, and Rebecca Willett. “Generalization error analysis for FDR controlled classification,” IEEE Statistical Signal Processing Workshop (SSP), 2007.

Kalyani Krishnamurthy and Rebecca Willett. “Multiscale reconstruction for photon-limited hyperspectral data,” IEEE Statistical Signal Processing Workshop (SSP), 2007.

Michael Gehm, Renu John, David Brady, Rebecca Willett, and Timothy Schultz. ” Single-shot compressive spectral imaging with a dual-disperser architecture,” Optics Express, Vol. 15, No. 21, pp. 14013-14027, 2007.

Rebecca Willett. “Multiscale intensity estimation for multi-photon microscopy,ISBI 2007.

Rebecca Willett, Michael Gehm, and David Brady. “Multiscale reconstruction for computational spectral imaging,SPIE Electronic Imaging 2007, Computational Imaging V.

Rebecca Willett. “Multiscale intensity estimation for marked Poisson processes,ICASSP 2007.

Rebecca Willett. “Multiscale reconstruction for photon-limited shifted excitation Raman spectroscopy,ICASSP 2007.

2006

Rebecca Willett. “Multiscale Analysis of Photon-Limited Astronomical Images,Statistical Challenges in Modern Astronomy (SCMA) IV.

Mohan Shankar, Rebecca Willett, Nikos Pitsianis, Robert Te Kolste, C. Chen, Robert Gibbons, and David Brady. “Ultra-thin Multiple-channel LWIR Imaging Systems,SPIE Optics and Photonics 2006.

Paul Barford, Robert Nowak, Rebecca Willett, and Vinod Yegneswaran. “Toward a Model for Sources of Internet Background Radiation” in Proceedings of the Passive and Active Measurement Conference (PAM ’06).

2005

Faster Rates in Regression via Active Learning” with R. Castro and R. Nowak, in NIPS 2005.

Faster Rates in Regression via Active Learning” with R. Castro and R. Nowak, University of Wisconsin Technical Report ECE-05-3.

Level Set Estimation in Medical Imaging” with R. Nowak, SSP 2005.

Minimax Optimal Level Set Estimation” with R. Nowak, in Wavelets XI at the SPIE Annual Meeting.

Multiresolution Methods for Recovering Signals and Sets from Noisy Observations” Ph.D. Thesis, Rice University.

Level Set Estimation via Trees” with R. Nowak, ICASSP 2005.

2004

Fast, Near-Optimal, Multiresolution Estimation of Poisson Signals and Images” with R. Nowak, EUSIPCO 2004.

Adaptive Sampling for Wireless Sensor Networks” with A. Martin and R. Nowak, ISIT 2004.

Complexity-Regularized Multiresolution Density Estimation” with R. Nowak, ISIT 2004.

Estimating Inhomogeneous Fields Using Wireless Sensor Networks” with R. Nowak and U. Mitra, IEEE Journal on Selected Areas in Communications, Special Issue on Fundamental Performance Limits of Wireless Sensor Networks.

Coarse-to-Fine Manifold Learning” with R. Castro and R. Nowak, ICASSP 2004 .

Backcasting: Adaptive Sampling for Sensor Networks” with A. Martin and R. Nowak, IPSN 2004 .

Fast Multiresolution Photon-Limited Image Reconstruction” with R. Nowak, ISBI 2004 .

2003

Backcasting: A New Approach to Energy Conservation in Sensor Networks” with A. Martin and R. Nowak, University of Wisconsin Technical Report ECE-03-4.

Wavelet-Based Superresolution in Astronomy” with I. Jermyn, R. Nowak, and J. Zerubia, in Astronomical Data Analysis Software and Systems (ADASS) 2003.

Multiscale Likelihood Analysis and Image Reconstruction” with R. Nowak, in Wavelets X at the SPIE Annual Meeting.

Multiscale Density Estimation” with R. Nowak, Technical Report TREE0303

Platelets: a multiscale approach for recovering edges and surfaces in photon-limited medical imaging” with R. Nowak, in IEEE Transactions on Medical Imaging, Volume: 22, Issue: 3 , March 2003, Page(s): 332 -350.

CORT: Classification Or Regression Trees” with C. Scott and R. Nowak, in ICASSP 2003.

2002

Multiscale Analysis for Intensity and Density Estimation” MS Thesis, Rice University, April 2002.

Platelets for Multiscale Analysis in Medical Imaging” with R. Nowak, presented at EMBS-BMES 2002.

Platelets for Multiscale Analysis in Photon-Limited Imaging” with R. Nowak, presented at ICIP 2002.

Multiresolution Nonparametric Intensity and Density Estimation” with R. Nowak, presented at ICASSP 2002.

2001

Platelets: A Multiscale Approach for Recovering Edges and Surfaces in Photon Limited Medical Imaging” with R. Nowak, Technical Report TREE0105

 

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