Plug in estimation in high dimensional linear inverse problems a rigorous analysis
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Publication:5854126
DOI10.1088/1742-5468/ab321azbMath1459.65079arXiv1806.10466OpenAlexW3102442912WikidataQ108743437 ScholiaQ108743437MaRDI QIDQ5854126
Philip Schniter, Alyson K. Fletcher, Sundeep Rangan, Subrata Sarkar, Parthe Pandit
Publication date: 16 March 2021
Published in: Journal of Statistical Mechanics: Theory and Experiment (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1806.10466
Linear regression; mixed models (62J05) Numerical solution to inverse problems in abstract spaces (65J22)
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- PhaseLift: Exact and Stable Signal Recovery from Magnitude Measurements via Convex Programming
- From Denoising to Compressed Sensing
- Approximate Message Passing With Consistent Parameter Estimation and Applications to Sparse Learning
- Blind Deconvolution Using Convex Programming
- Accurate Prediction of Phase Transitions in Compressed Sensing via a Connection to Minimax Denoising
- A Singular Value Thresholding Algorithm for Matrix Completion
- Self-calibration and biconvex compressive sensing
- Sparsity-Cognizant Total Least-Squares for Perturbed Compressive Sampling
- Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising
- AMP-Inspired Deep Networks for Sparse Linear Inverse Problems
- Hybrid Approximate Message Passing
- Joint Channel-Estimation and Equalization of Single-Carrier Systems via Bilinear AMP
- State evolution for general approximate message passing algorithms, with applications to spatial coupling
- The Dynamics of Message Passing on Dense Graphs, with Applications to Compressed Sensing