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Compressed Sensing

72 directly classified papers

Papers per year

Papers

How Much Restricted Isometry is Needed In Nonconvex Matrix Recovery? NIPS 2018
Learning without the Phase: Regularized PhaseMax Achieves Optimal Sample Complexity NIPS 2018
Phase Retrieval Under a Generative Prior NIPS 2018
Plug-in Estimation in High-Dimensional Linear Inverse Problems: A Rigorous Analysis NIPS 2018
Solving Most Systems of Random Quadratic Equations NIPS 2017
Learned D-AMP: Principled Neural Network based Compressive Image Recovery NIPS 2017
On Blackbox Backpropagation and Jacobian Sensing NIPS 2017
Simple strategies for recovering inner products from coarsely quantized random projections NIPS 2017
Fitting Low-Rank Tensors in Constant Time NIPS 2017
Near Optimal Sketching of Low-Rank Tensor Regression NIPS 2017
Convolutional Phase Retrieval NIPS 2017
Fast recovery from a union of subspaces NIPS 2016
Limits on Sparse Support Recovery via Linear Sketching with Random Expander Matrices AISTATS 2016
Sparse Support Recovery with Non-smooth Loss Functions NIPS 2016
b-bit Marginal Regression NIPS 2015
LASSO with Non-linear Measurements is Equivalent to One With Linear Measurements NIPS 2015
Super-Resolution Off the Grid NIPS 2015
Regularization-Free Estimation in Trace Regression with Symmetric Positive Semidefinite Matrices NIPS 2015
Towards a Lower Sample Complexity for Robust One-bit Compressed Sensing ICML 2015
Ambient Occlusion via Compressive Visibility Estimation CVPR 2015
Robust PCA with compressed data NIPS 2015
Reweighted Laplace Prior Based Hyperspectral Compressive Sensing for Unknown Sparsity CVPR 2015
FPA-CS: Focal Plane Array-Based Compressive Imaging in Short-Wave Infrared CVPR 2015
Low-Cost Compressive Sensing for Color Video and Depth CVPR 2014
Compressive Sensing of Signals from a GMM with Sparse Precision Matrices NIPS 2014