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Convex and Nonconvex Optimization Are Both Minimax-Optimal for Noisy
  Blind Deconvolution under Random Designs
v1v2 (latest)

Convex and Nonconvex Optimization Are Both Minimax-Optimal for Noisy Blind Deconvolution under Random Designs

4 August 2020
Yuxin Chen
Jianqing Fan
B. Wang
Yuling Yan
ArXiv (abs)PDFHTML

Papers citing "Convex and Nonconvex Optimization Are Both Minimax-Optimal for Noisy Blind Deconvolution under Random Designs"

10 / 10 papers shown
Low solution rank of the matrix LASSO under RIP with consequences for
  rank-constrained algorithms
Low solution rank of the matrix LASSO under RIP with consequences for rank-constrained algorithms
Andrew D. McRae
269
2
0
19 Apr 2024
How robust is randomized blind deconvolution via nuclear norm
  minimization against adversarial noise?
How robust is randomized blind deconvolution via nuclear norm minimization against adversarial noise?Applied and Computational Harmonic Analysis (ACHA), 2023
Julia Kostin
Felix Krahmer
Dominik Stöger
259
1
0
17 Mar 2023
Deflated HeteroPCA: Overcoming the curse of ill-conditioning in
  heteroskedastic PCA
Deflated HeteroPCA: Overcoming the curse of ill-conditioning in heteroskedastic PCAAnnals of Statistics (Ann. Stat.), 2023
Yuchen Zhou
Yuxin Chen
373
11
0
10 Mar 2023
Optimal tuning-free convex relaxation for noisy matrix completion
Optimal tuning-free convex relaxation for noisy matrix completionIEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2022
Yuepeng Yang
Cong Ma
399
8
0
12 Jul 2022
Robust Matrix Completion with Heavy-tailed Noise
Robust Matrix Completion with Heavy-tailed NoiseJournal of the American Statistical Association (JASA), 2022
Bingyan Wang
Jianqing Fan
281
16
0
09 Jun 2022
Sample-Efficient Reinforcement Learning for Linearly-Parameterized MDPs
  with a Generative Model
Sample-Efficient Reinforcement Learning for Linearly-Parameterized MDPs with a Generative ModelNeural Information Processing Systems (NeurIPS), 2021
Bingyan Wang
Yuling Yan
Jianqing Fan
512
24
0
28 May 2021
Spectral Methods for Data Science: A Statistical Perspective
Spectral Methods for Data Science: A Statistical Perspective
Yuxin Chen
Yuejie Chi
Jianqing Fan
Cong Ma
699
217
0
15 Dec 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 DataAnnals of Statistics (Ann. Stat.), 2020
Yuxin Chen
Jianqing Fan
Cong Ma
Yuling Yan
538
59
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 EfficientlyIEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2019
Laixi Shi
Yuejie Chi
492
26
0
25 Nov 2019
Nonconvex Matrix Factorization from Rank-One Measurements
Nonconvex Matrix Factorization from Rank-One Measurements
Yuanxin Li
Cong Ma
Yuxin Chen
Yuejie Chi
220
58
0
17 Feb 2018
1
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