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Error Bound of Empirical $\ell_2$ Risk Minimization for Noisy Standard
  and Generalized Phase Retrieval Problems

Error Bound of Empirical ℓ2\ell_2ℓ2​ Risk Minimization for Noisy Standard and Generalized Phase Retrieval Problems

27 May 2022
Junren Chen
Michael Kwok-Po Ng
ArXivPDFHTML

Papers citing "Error Bound of Empirical $\ell_2$ Risk Minimization for Noisy Standard and Generalized Phase Retrieval Problems"

3 / 3 papers shown
Title
A Shrinkage Principle for Heavy-Tailed Data: High-Dimensional Robust
  Low-Rank Matrix Recovery
A Shrinkage Principle for Heavy-Tailed Data: High-Dimensional Robust Low-Rank Matrix Recovery
Jianqing Fan
Weichen Wang
Ziwei Zhu
49
96
0
28 Mar 2016
Learning without Concentration for General Loss Functions
Learning without Concentration for General Loss Functions
S. Mendelson
63
65
0
13 Oct 2014
Learning without Concentration
Learning without Concentration
S. Mendelson
92
333
0
01 Jan 2014
1