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Square Deal: Lower Bounds and Improved Relaxations for Tensor Recovery

Square Deal: Lower Bounds and Improved Relaxations for Tensor Recovery

22 July 2013
Cun Mu
Bo Huang
John N. Wright
D. Goldfarb
ArXivPDFHTML

Papers citing "Square Deal: Lower Bounds and Improved Relaxations for Tensor Recovery"

16 / 16 papers shown
Title
Information-Theoretic Guarantees for Recovering Low-Rank Tensors from Symmetric Rank-One Measurements
Information-Theoretic Guarantees for Recovering Low-Rank Tensors from Symmetric Rank-One Measurements
Eren C. Kızıldağ
79
0
0
07 Feb 2025
Learnable Scaled Gradient Descent for Guaranteed Robust Tensor PCA
Learnable Scaled Gradient Descent for Guaranteed Robust Tensor PCA
Lanlan Feng
Ce Zhu
Yipeng Liu
Saiprasad Ravishankar
Longxiu Huang
58
0
0
20 Jan 2025
Low-Tubal-Rank Tensor Recovery via Factorized Gradient Descent
Low-Tubal-Rank Tensor Recovery via Factorized Gradient Descent
Zhiyu Liu
Zhi Han
Yandong Tang
Xi-Le Zhao
Yao Wang
72
1
0
22 Jan 2024
ISLET: Fast and Optimal Low-rank Tensor Regression via Importance
  Sketching
ISLET: Fast and Optimal Low-rank Tensor Regression via Importance Sketching
Anru R. Zhang
Yuetian Luo
Garvesh Raskutti
M. Yuan
129
44
0
09 Nov 2019
Parallel matrix factorization for low-rank tensor completion
Parallel matrix factorization for low-rank tensor completion
Yangyang Xu
Ruru Hao
W. Yin
Zhixun Su
50
343
0
04 Dec 2013
Robust Low-rank Tensor Recovery: Models and Algorithms
Robust Low-rank Tensor Recovery: Models and Algorithms
D. Goldfarb
Zhiwei Qin
80
389
0
24 Nov 2013
Tensor-based formulation and nuclear norm regularization for
  multi-energy computed tomography
Tensor-based formulation and nuclear norm regularization for multi-energy computed tomography
O. Semerci
Ning Hao
M. Kilmer
Eric L. Miller
MedIm
53
350
0
19 Jul 2013
A New Convex Relaxation for Tensor Completion
A New Convex Relaxation for Tensor Completion
Bernardino Romera-Paredes
Massimiliano Pontil
51
179
0
17 Jul 2013
Tensor decompositions for learning latent variable models
Tensor decompositions for learning latent variable models
Anima Anandkumar
Rong Ge
Daniel J. Hsu
Sham Kakade
Matus Telgarsky
273
1,142
0
29 Oct 2012
Estimation of Simultaneously Sparse and Low Rank Matrices
Estimation of Simultaneously Sparse and Low Rank Matrices
E. Richard
Pierre-André Savalle
Nicolas Vayatis
68
203
0
27 Jun 2012
Strongly Convex Programming for Exact Matrix Completion and Robust
  Principal Component Analysis
Strongly Convex Programming for Exact Matrix Completion and Robust Principal Component Analysis
Hui Zhang
Jian-Feng Cai
Lizhi Cheng
Jubo Zhu
67
30
0
16 Dec 2011
The Convex Geometry of Linear Inverse Problems
The Convex Geometry of Linear Inverse Problems
V. Chandrasekaran
Benjamin Recht
P. Parrilo
A. Willsky
148
1,338
0
03 Dec 2010
A Unified Framework for High-Dimensional Analysis of M-Estimators with
  Decomposable Regularizers
A Unified Framework for High-Dimensional Analysis of M-Estimators with Decomposable Regularizers
S. Negahban
Pradeep Ravikumar
Martin J. Wainwright
Bin Yu
280
1,377
0
13 Oct 2010
Estimation of low-rank tensors via convex optimization
Estimation of low-rank tensors via convex optimization
Ryota Tomioka
K. Hayashi
H. Kashima
151
208
0
05 Oct 2010
Observed Universality of Phase Transitions in High-Dimensional Geometry,
  with Implications for Modern Data Analysis and Signal Processing
Observed Universality of Phase Transitions in High-Dimensional Geometry, with Implications for Modern Data Analysis and Signal Processing
D. Donoho
Jared Tanner
79
462
0
14 Jun 2009
Guaranteed Minimum-Rank Solutions of Linear Matrix Equations via Nuclear
  Norm Minimization
Guaranteed Minimum-Rank Solutions of Linear Matrix Equations via Nuclear Norm Minimization
Benjamin Recht
Maryam Fazel
P. Parrilo
256
3,762
0
28 Jun 2007
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