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Composite optimization for robust blind deconvolution
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Composite optimization for robust blind deconvolution

Vasileios Charisopoulos
Damek Davis
Mateo Díaz
Dmitriy Drusvyatskiy
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Papers citing "Composite optimization for robust blind deconvolution"

13 / 13 papers shown
Title
Robust Low-rank Tensor Train Recovery
Robust Low-rank Tensor Train Recovery
Zhen Qin
Zhihui Zhu
72
1
0
19 Oct 2024
A New Inexact Proximal Linear Algorithm with Adaptive Stopping Criteria for Robust Phase Retrieval
A New Inexact Proximal Linear Algorithm with Adaptive Stopping Criteria for Robust Phase Retrieval
Zhong Zheng
Shiqian Ma
Lingzhou Xue
21
6
0
25 Apr 2023
Spectral Methods for Data Science: A Statistical Perspective
Spectral Methods for Data Science: A Statistical Perspective
Yuxin Chen
Yuejie Chi
Jianqing Fan
Cong Ma
153
173
0
15 Dec 2020
Convex and Nonconvex Optimization Are Both Minimax-Optimal for Noisy Blind Deconvolution under Random Designs
Convex and Nonconvex Optimization Are Both Minimax-Optimal for Noisy Blind Deconvolution under Random Designs
Yuxin Chen
Jianqing Fan
B. Wang
Yuling Yan
90
16
0
04 Aug 2020
A Manifold Proximal Linear Method for Sparse Spectral Clustering with Application to Single-Cell RNA Sequencing Data Analysis
A Manifold Proximal Linear Method for Sparse Spectral Clustering with Application to Single-Cell RNA Sequencing Data Analysis
Zhongruo Wang
Bingyuan Liu
Shixiang Chen
Shiqian Ma
Lingzhou Xue
Hongyu Zhao
49
22
0
18 Jul 2020
From Symmetry to Geometry: Tractable Nonconvex Problems
From Symmetry to Geometry: Tractable Nonconvex Problems
Yuqian Zhang
Qing Qu
John N. Wright
87
45
0
14 Jul 2020
Understanding Notions of Stationarity in Non-Smooth Optimization
Understanding Notions of Stationarity in Non-Smooth Optimization
Jiajin Li
Anthony Man-Cho So
Wing-Kin Ma
52
47
0
26 Jun 2020
Bridging Convex and Nonconvex Optimization in Robust PCA: Noise, Outliers, and Missing Data
Bridging Convex and Nonconvex Optimization in Robust PCA: Noise, Outliers, and Missing Data
Yuxin Chen
Jianqing Fan
Cong Ma
Yuling Yan
89
52
0
15 Jan 2020
Manifold Gradient Descent Solves Multi-Channel Sparse Blind Deconvolution Provably and Efficiently
Manifold Gradient Descent Solves Multi-Channel Sparse Blind Deconvolution Provably and Efficiently
Laixi Shi
Yuejie Chi
86
26
0
25 Nov 2019
Weakly Convex Optimization over Stiefel Manifold Using Riemannian Subgradient-Type Methods
Weakly Convex Optimization over Stiefel Manifold Using Riemannian Subgradient-Type Methods
Xiao Li
Shixiang Chen
Zengde Deng
Qing Qu
Zhihui Zhu
Anthony Man-Cho So
78
15
0
12 Nov 2019
Stochastic algorithms with geometric step decay converge linearly on sharp functions
Stochastic algorithms with geometric step decay converge linearly on sharp functions
Damek Davis
Dmitriy Drusvyatskiy
Vasileios Charisopoulos
73
28
0
22 Jul 2019
Low-rank matrix recovery with composite optimization: good conditioning and rapid convergence
Low-rank matrix recovery with composite optimization: good conditioning and rapid convergence
Vasileios Charisopoulos
Yudong Chen
Damek Davis
Mateo Díaz
Lijun Ding
Dmitriy Drusvyatskiy
88
85
0
22 Apr 2019
Nonconvex Optimization Meets Low-Rank Matrix Factorization: An Overview
Nonconvex Optimization Meets Low-Rank Matrix Factorization: An Overview
Yuejie Chi
Yue M. Lu
Yuxin Chen
75
427
0
25 Sep 2018