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Phase Transitions of Spectral Initialization for High-Dimensional
  Nonconvex Estimation

Phase Transitions of Spectral Initialization for High-Dimensional Nonconvex Estimation

21 February 2017
Yue M. Lu
Gen Li
ArXivPDFHTML

Papers citing "Phase Transitions of Spectral Initialization for High-Dimensional Nonconvex Estimation"

12 / 12 papers shown
Title
Computational and Statistical Guarantees for Tensor-on-Tensor Regression with Tensor Train Decomposition
Computational and Statistical Guarantees for Tensor-on-Tensor Regression with Tensor Train Decomposition
Zhen Qin
Zhihui Zhu
74
4
0
10 Jun 2024
Misspecified Phase Retrieval with Generative Priors
Misspecified Phase Retrieval with Generative Priors
Zhaoqiang Liu
Xinshao Wang
Jiulong Liu
43
4
0
11 Oct 2022
Compressing Sign Information in DCT-based Image Coding via Deep Sign
  Retrieval
Compressing Sign Information in DCT-based Image Coding via Deep Sign Retrieval
Kei Suzuki
Chihiro Tsutake
Keita Takahashi
T. Fujii
23
3
0
21 Sep 2022
Estimation in Rotationally Invariant Generalized Linear Models via
  Approximate Message Passing
Estimation in Rotationally Invariant Generalized Linear Models via Approximate Message Passing
R. Venkataramanan
Kevin Kögler
Marco Mondelli
19
32
0
08 Dec 2021
Generalization Guarantees for Neural Architecture Search with
  Train-Validation Split
Generalization Guarantees for Neural Architecture Search with Train-Validation Split
Samet Oymak
Mingchen Li
Mahdi Soltanolkotabi
AI4CE
OOD
36
13
0
29 Apr 2021
HePPCAT: Probabilistic PCA for Data with Heteroscedastic Noise
HePPCAT: Probabilistic PCA for Data with Heteroscedastic Noise
David Hong
Kyle Gilman
Laura Balzano
Jeffrey A. Fessler
34
19
0
10 Jan 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
40
165
0
15 Dec 2020
How to iron out rough landscapes and get optimal performances: Averaged
  Gradient Descent and its application to tensor PCA
How to iron out rough landscapes and get optimal performances: Averaged Gradient Descent and its application to tensor PCA
Giulio Biroli
C. Cammarota
F. Ricci-Tersenghi
36
27
0
29 May 2019
Analysis of Spectral Methods for Phase Retrieval with Random Orthogonal
  Matrices
Analysis of Spectral Methods for Phase Retrieval with Random Orthogonal Matrices
Rishabh Dudeja
Milad Bakhshizadeh
Junjie Ma
A. Maleki
19
20
0
07 Mar 2019
Lifting high-dimensional nonlinear models with Gaussian regressors
Lifting high-dimensional nonlinear models with Gaussian regressors
Christos Thrampoulidis
A. S. Rawat
21
8
0
11 Dec 2017
Solving Almost all Systems of Random Quadratic Equations
Solving Almost all Systems of Random Quadratic Equations
G. Wang
G. Giannakis
Y. Saad
Jie Chen
29
25
0
29 May 2017
The Projected Power Method: An Efficient Algorithm for Joint Alignment
  from Pairwise Differences
The Projected Power Method: An Efficient Algorithm for Joint Alignment from Pairwise Differences
Yuxin Chen
Emmanuel Candes
37
92
0
19 Sep 2016
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