Compressed sensing in noisy imaging environments. - Jarvis D. Haupt; Rui M. Castro; Robert D. Nowak (Computational Imaging, 2006)

A Universal Matched Source-Channel Communication Scheme for Wireless Sensor Ensembles. - Waheed Uz Zaman Bajwa; Jarvis D. Haupt; Akbar M. Sayeed; Robert D. Nowak (ICASSP (5), 2006)

Compressed Sensing Vs. Active Learning. - Rui M. Castro; Jarvis D. Haupt; Robert D. Nowak (ICASSP (3), 2006)

Compressive Sampling Vs. Conventional Imaging. - Jarvis D. Haupt; Robert D. Nowak (ICIP, 2006)

Compressive wireless sensing. - Waheed Uz Zaman Bajwa; Jarvis D. Haupt; Akbar M. Sayeed; Robert D. Nowak (IPSN, 2006)

Decentralized compression and predistribution via randomized gossiping. - Michael G. Rabbat; Jarvis D. Haupt; Aarti Singh; Robert D. Nowak (IPSN, 2006)

Signal Reconstruction From Noisy Random Projections. - Jarvis D. Haupt; Robert D. Nowak (IEEE Trans. Inf. Theory, 2006)

Compressive Sampling for Signal Detection. - Jarvis D. Haupt; Robert D. Nowak (ICASSP (3), 2007)

Joint Source-Channel Communication for Distributed Estimation in Sensor Networks. - Waheed Uz Zaman Bajwa; Jarvis D. Haupt; Akbar M. Sayeed; Robert D. Nowak (IEEE Trans. Inf. Theory, 2007)

Adaptive discovery of sparse signals in noise. - Jarvis D. Haupt; Rui M. Castro; Robert D. Nowak (ACSCC, 2008)

Compressed channel sensing. - Waheed Uz Zaman Bajwa; Jarvis D. Haupt; Gil M. Raz; Robert D. Nowak (CISS, 2008)

Finding needles in noisy haystacks. - Rui M. Castro; Jarvis D. Haupt; Robert D. Nowak; Gil M. Raz (ICASSP, 2008)

Compressed Sensing for Networked Data. - Jarvis D. Haupt; Waheed U. Bajwa; Michael G. Rabbat; Robert D. Nowak (IEEE Signal Process. Mag., 2008)

Distilled sensing: selective sampling for sparse signal recovery. - Jarvis D. Haupt; Rui M. Castro; Robert D. Nowak (AISTATS, 2009)

On the Restricted Isometry of deterministically subsampled Fourier matrices. - Jarvis D. Haupt; Lorne Applebaum; Robert D. Nowak (CISS, 2010)

Improved bounds for sparse recovery from adaptive measurements. - Jarvis D. Haupt; Rui M. Castro; Robert D. Nowak (ISIT, 2010)

Compressed Channel Sensing: A New Approach to Estimating Sparse Multipath Channels. - Waheed Uz Zaman Bajwa; Jarvis D. Haupt; Akbar M. Sayeed; Robert D. Nowak (Proc. IEEE, 2010)

Toeplitz Compressed Sensing Matrices With Applications to Sparse Channel Estimation. - Jarvis D. Haupt; Waheed Uz Zaman Bajwa; Gil M. Raz; Robert D. Nowak (IEEE Trans. Inf. Theory, 2010)

Session MP4a: Compressive sensing applications in networking. - Jarvis D. Haupt (ACSCC, 2011)

Session TA8b3: Adaptive sensing. - Jarvis D. Haupt (ACSCC, 2011)

Efficient adaptive compressive sensing using sparse hierarchical learned dictionaries. - Akshay Soni; Jarvis D. Haupt (ACSCC, 2011)

Robust support recovery using sparse compressive sensing matrices. - Jarvis D. Haupt; Richard G. Baraniuk (CISS, 2011)

Deterministic pilot sequences for sparse channel estimation in OFDM systems. - Lorne Applebaum; Waheed U. Bajwa; A. Robert Calderbank; Jarvis D. Haupt; Robert Nowak 001 (DSP, 2011)

Distilled Sensing: Adaptive Sampling for Sparse Detection and Estimation. - Jarvis D. Haupt; Rui M. Castro; Robert D. Nowak (IEEE Trans. Inf. Theory, 2011)

Adaptive sensing for sparse recovery. - Jarvis D. Haupt; Robert D. Nowak (Compressed Sensing, 2012)

Learning sparse representations for adaptive compressive sensing. - Akshay Soni; Jarvis D. Haupt (ICASSP, 2012)

Level set estimation from compressive measurements using box constrained total variation regularization. - Akshay Soni; Jarvis D. Haupt (ICIP, 2012)

Sequentially designed compressed sensing. - Jarvis D. Haupt; Richard G. Baraniuk; Rui M. Castro; Robert D. Nowak (SSP, 2012)

Compressive measurement designs for estimating structured signals in structured clutter: A Bayesian Experimental Design approach. - Swayambhoo Jain; Akshay Soni; Jarvis D. Haupt (ACSSC, 2013)

Semi-blind source separation via sparse representations and online dictionary learning. - Sirisha Rambhatla; Jarvis D. Haupt (ACSSC, 2013)

Locating salient items in large data collections with compressive linear measurements. - Jarvis D. Haupt (CAMSAP, 2013)

Fundamental limits for support recovery of tree-sparse signals from noisy compressive samples. - Akshay Soni; Jarvis D. Haupt (GlobalSIP, 2013)

Automated Defect Localization via Low Rank Plus Outlier Modeling of Propagating Wavefield Data. - Stefano Gonella; Jarvis D. Haupt (CoRR, 2013)

Error bounds for maximum likelihood matrix completion under sparse factor models. - Akshay Soni; Swayambhoo Jain; Jarvis D. Haupt; Stefano Gonella (GlobalSIP, 2014)

Sparse dictionary learning from 1-BIT data. - Jarvis D. Haupt; Nikos D. Sidiropoulos; Georgios B. Giannakis (ICASSP, 2014)

Recycled linear classifiers for multiclass classification. - Akshay Soni; Jarvis D. Haupt; Fatih Porikli (ICASSP, 2014)

Estimation error guarantees for Poisson denoising with sparse and structured dictionary models. - Akshay Soni; Jarvis D. Haupt (ISIT, 2014)

Anomaly-Sensitive Dictionary Learning for Unsupervised Diagnostics of Solid Media. - Jeffrey M. Druce; Jarvis D. Haupt; Stefano Gonella (CoRR, 2014)

On the Fundamental Limits of Recovering Tree Sparse Vectors From Noisy Linear Measurements. - Akshay Soni; Jarvis D. Haupt (IEEE Trans. Inf. Theory, 2014)

Locating rare and weak material anomalies by convex demixing of propagating wavefields. - Mojtaba Kadkhodaie; Swayambhoo Jain; Jarvis D. Haupt; Jeffrey M. Druce; Stefano Gonella (CAMSAP, 2015)

Locating salient group-structured image features via adaptive compressive sensing. - Xingguo Li; Jarvis D. Haupt (GlobalSIP, 2015)

Active learning of self-concordant like multi-index functions. - Ilija Bogunovic; Volkan Cevher; Jarvis D. Haupt; Jonathan Scarlett (ICASSP, 2015)

Outlier identification via randomized adaptive compressive sampling. - Xingguo Li; Jarvis D. Haupt (ICASSP, 2015)

Identifying Outliers in Large Matrices via Randomized Adaptive Compressive Sampling. - Xingguo Li; Jarvis D. Haupt (IEEE Trans. Signal Process., 2015)

Robust PCA via tensor outlier pursuit. - Jineng Ren; Xingguo Li; Jarvis D. Haupt (ACSSC, 2016)

A dictionary based generalization of robust PCA. - Sirisha Rambhatla; Xingguo Li; Jarvis D. Haupt (GlobalSIP, 2016)

Stochastic Variance Reduced Optimization for Nonconvex Sparse Learning. - Xingguo Li; Tuo Zhao; Raman Arora; Han Liu 001; Jarvis D. Haupt (ICML, 2016)

A refined analysis for the sample complexity of adaptive compressive outlier sensing. - Xingguo Li; Jarvis D. Haupt (SSP, 2016)

Robust Low-Complexity Randomized Methods for Locating Outliers in Large Matrices. - Xingguo Li; Jarvis D. Haupt (CoRR, 2016)

A First Order Free Lunch for SQRT-Lasso. - Xingguo Li; Jarvis D. Haupt; Raman Arora; Han Liu 001; Mingyi Hong 001; Tuo Zhao (CoRR, 2016)

Symmetry, Saddle Points, and Global Geometry of Nonconvex Matrix Factorization. - Xingguo Li; Zhaoran Wang 001; Junwei Lu; Raman Arora; Jarvis D. Haupt; Han Liu 001; Tuo Zhao (CoRR, 2016)

Noisy Matrix Completion Under Sparse Factor Models. - Akshay Soni; Swayambhoo Jain; Jarvis D. Haupt; Stefano Gonella (IEEE Trans. Inf. Theory, 2016)

Target-based hyperspectral demixing via generalized robust PCA. - Sirisha Rambhatla; Xingguo Li; Jarvis D. Haupt (ACSSC, 2017)

Robust Low-Complexity methods for matrix column outlier identification. - Xingguo Li; Jarvis D. Haupt (CAMSAP, 2017)

Communication-Efficient distributed optimization for sparse learning via two-way truncation. - Jineng Ren; Xingguo Li; Jarvis D. Haupt (CAMSAP, 2017)

Group-level support recovery guarantees for group lasso estimator. - Mojtaba Kadkhodaie Elyaderani; Swayambhoo Jain; Jeffrey M. Druce; Stefano Gonella; Jarvis D. Haupt (ICASSP, 2017)

Convolutional approximations to linear dimensionality reduction operators. - Swayambhoo Jain; Jarvis D. Haupt (ICASSP, 2017)

Noisy tensor completion for tensors with a sparse canonical polyadic factor. - Swayambhoo Jain; Alexander Gutierrez; Jarvis D. Haupt (ISIT, 2017)

Near Optimal Sketching of Low-Rank Tensor Regression. - Xingguo Li; Jarvis D. Haupt; David P. Woodruff (NIPS, 2017)

On Quadratic Convergence of DC Proximal Newton Algorithm in Nonconvex Sparse Learning. - Xingguo Li; Lin Yang 011; Jason Ge; Jarvis D. Haupt; Tong Zhang 001; Tuo Zhao (NIPS, 2017)

On Quadratic Convergence of DC Proximal Newton Algorithm for Nonconvex Sparse Learning in High Dimensions. - Xingguo Li; Lin F. Yang; Jason Ge; Jarvis D. Haupt; Tong Zhang 001; Tuo Zhao (CoRR, 2017)

Improved Support Recovery Guarantees for the Group Lasso With Applications to Structural Health Monitoring. - Mojtaba Kadkhodaie Elyaderani; Swayambhoo Jain; Jeffrey M. Druce; Stefano Gonella; Jarvis D. Haupt (CoRR, 2017)

Communication-efficient Algorithm for Distributed Sparse Learning via Two-way Truncation. - Jineng Ren; Jarvis D. Haupt (CoRR, 2017)

A Compressed Sensing Based Decomposition of Electrodermal Activity Signals. - Swayambhoo Jain; Urvashi Oswal; Kevin S. Xu 001; Brian Eriksson; Jarvis D. Haupt (IEEE Trans. Biomed. Eng., 2017)

Zeroth-Order Stochastic Projected Gradient Descent for Nonconvex Optimization. - Sijia Liu 001; Xingguo Li; Pin-Yu Chen; Jarvis D. Haupt; Lisa Amini (GlobalSIP, 2018)

Fast Asynchronous Decentralized Optimization: Allowing Multiple Masters. - Meng Ma; Jineng Ren; Georgios B. Giannakis; Jarvis D. Haupt (GlobalSIP, 2018)

TensorMap: LIDAR-Based Topological Mapping and Localization via Tensor Decompositions. - Sirisha Rambhatla; Nikos D. Sidiropoulos; Jarvis D. Haupt (GlobalSIP, 2018)

Provably Communication-Efficient Asynchronous Distributed Inference for Convex and Nonconvex Problems. - Jineng Ren; Jarvis D. Haupt (GlobalSIP, 2018)

Robust PCA via Dictionary Based Outlier Pursuit. - Xingguo Li; Jineng Ren; Sirisha Rambhatla; Yangyang Xu; Jarvis D. Haupt (ICASSP, 2018)

On Landscape of Lagrangian Functions and Stochastic Search for Constrained Nonconvex Optimization. - Zhehui Chen; Xingguo Li; Lin F. Yang; Jarvis D. Haupt; Tuo Zhao (CoRR, 2018)

On Tighter Generalization Bound for Deep Neural Networks: CNNs, ResNets, and Beyond. - Xingguo Li; Junwei Lu; Zhaoran Wang 001; Jarvis D. Haupt; Tuo Zhao (CoRR, 2018)

Minimax Lower Bounds for Noisy Matrix Completion Under Sparse Factor Models. - Abhinav V. Sambasivan; Jarvis D. Haupt (IEEE Trans. Inf. Theory, 2018)

Sketching Dictionary Based Robust PCA in Large Matrices. - Xingguo Li; Jarvis D. Haupt (ACSSC, 2019)

Computer Graphics meets Estimation Theory: Parameter Estimation Lower Bounds for Plenoptic Imaging Systems. - Abhinav V. Sambasivan; Richard G. Paxman; Jarvis D. Haupt (ACSSC, 2019)

On Constrained Nonconvex Stochastic Optimization: A Case Study for Generalized Eigenvalue Decomposition. - Zhehui Chen; Xingguo Li; Lin Yang 011; Jarvis D. Haupt; Tuo Zhao (AISTATS, 2019)

NOODL: Provable Online Dictionary Learning and Sparse Coding. - Sirisha Rambhatla; Xingguo Li; Jarvis D. Haupt (ICLR (Poster), 2019)

On Fast Convergence of Proximal Algorithms for SQRT-Lasso Optimization: Don't Worry About its Nonsmooth Loss Function. - Xingguo Li; Haoming Jiang; Jarvis D. Haupt; Raman Arora; Han Liu 001; Mingyi Hong 001; Tuo Zhao (UAI, 2019)

A Dictionary-Based Generalization of Robust PCA Part I: Study of Theoretical Properties. - Sirisha Rambhatla; Xingguo Li; Jineng Ren; Jarvis D. Haupt (CoRR, 2019)

A Dictionary-Based Generalization of Robust PCA Part II: Applications to Hyperspectral Demixing. - Sirisha Rambhatla; Xingguo Li; Jineng Ren; Jarvis D. Haupt (CoRR, 2019)

Symmetry, Saddle Points, and Global Optimization Landscape of Nonconvex Matrix Factorization. - Xingguo Li; Junwei Lu; Raman Arora; Jarvis D. Haupt; Han Liu 001; Zhaoran Wang 001; Tuo Zhao (IEEE Trans. Inf. Theory, 2019)

Provable Online CP/PARAFAC Decomposition of a Structured Tensor via Dictionary Learning. - Sirisha Rambhatla; Xingguo Li; Jarvis D. Haupt (NeurIPS, 2020)

Convexifying Sparse Interpolation With Infinitely Wide Neural Networks: An Atomic Norm Approach. - Akshay Kumar; Jarvis D. Haupt (IEEE Signal Process. Lett., 2020)

A Dictionary-Based Generalization of Robust PCA With Applications to Target Localization in Hyperspectral Imaging. - Sirisha Rambhatla; Xingguo Li; Jineng Ren; Jarvis D. Haupt (IEEE Trans. Signal Process., 2020)

A Provably Communication-Efficient Asynchronous Distributed Inference Method for Convex and Nonconvex Problems. - Jineng Ren; Jarvis D. Haupt (IEEE Trans. Signal Process., 2020)

Communication-efficient hierarchical distributed optimization for multi-agent policy evaluation. - Jineng Ren; Jarvis D. Haupt; Zehua Guo 001 (J. Comput. Sci., 2021)

Reducing the Complexity of Model-Based MRI Reconstructions via Sparsification. - Alex Gutierrez; Michael Mullen; Di Xiao 002; Albert Jang; Taylor Froelich; Michael Garwood; Jarvis D. Haupt (IEEE Trans. Medical Imaging, 2021)

Directional Convergence Near Small Initializations and Saddles in Two-Homogeneous Neural Networks. - Akshay Kumar; Jarvis D. Haupt (Trans. Mach. Learn. Res., 2024)

Early Directional Convergence in Deep Homogeneous Neural Networks for Small Initializations. - Akshay Kumar; Jarvis D. Haupt (Trans. Mach. Learn. Res., 2025)

Towards Understanding Gradient Flow Dynamics of Homogeneous Neural Networks Beyond the Origin. - Akshay Kumar; Jarvis D. Haupt (CoRR, 2025)