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Low-rank Matrix Completion using Alternating Minimization

Low-rank Matrix Completion using Alternating Minimization

3 December 2012
Prateek Jain
Praneeth Netrapalli
Sujay Sanghavi
ArXiv (abs)PDFHTML

Papers citing "Low-rank Matrix Completion using Alternating Minimization"

50 / 407 papers shown
Title
Bootstrapping the error of Oja's algorithm
Bootstrapping the error of Oja's algorithm
Robert Lunde
Purnamrita Sarkar
Rachel A. Ward
100
11
0
28 Jun 2021
Temporal Graph Signal Decomposition
Temporal Graph Signal Decomposition
Maxwell McNeil
Lin Zhang
Petko Bogdanov
41
15
0
25 Jun 2021
GNMR: A provable one-line algorithm for low rank matrix recovery
GNMR: A provable one-line algorithm for low rank matrix recovery
Pini Zilber
B. Nadler
133
14
0
24 Jun 2021
Stable and Interpretable Unrolled Dictionary Learning
Stable and Interpretable Unrolled Dictionary Learning
Bahareh Tolooshams
Demba E. Ba
77
16
0
31 May 2021
Principal Component Hierarchy for Sparse Quadratic Programs
Principal Component Hierarchy for Sparse Quadratic Programs
R. Vreugdenhil
Viet Anh Nguyen
Armin Eftekhari
Peyman Mohajerin Esfahani
72
2
0
25 May 2021
Lecture notes on non-convex algorithms for low-rank matrix recovery
Lecture notes on non-convex algorithms for low-rank matrix recovery
Irène Waldspurger
58
1
0
21 May 2021
Sample Efficient Linear Meta-Learning by Alternating Minimization
Sample Efficient Linear Meta-Learning by Alternating Minimization
K. K. Thekumparampil
Prateek Jain
Praneeth Netrapalli
Sewoong Oh
60
23
0
18 May 2021
Exact Recovery in the General Hypergraph Stochastic Block Model
Exact Recovery in the General Hypergraph Stochastic Block Model
Q. Zhang
Vincent Y. F. Tan
96
22
0
11 May 2021
Matrix completion based on Gaussian parameterized belief propagation
Matrix completion based on Gaussian parameterized belief propagation
Koki Okajima
Y. Kabashima
11
0
0
01 May 2021
Sharp Global Guarantees for Nonconvex Low-rank Recovery in the Noisy Overparameterized Regime
Sharp Global Guarantees for Nonconvex Low-rank Recovery in the Noisy Overparameterized Regime
Richard Y. Zhang
116
25
0
21 Apr 2021
Multi-target prediction for dummies using two-branch neural networks
Multi-target prediction for dummies using two-branch neural networks
Dimitrios Iliadis
B. De Baets
Willem Waegeman
44
11
0
19 Apr 2021
Deep Distribution-preserving Incomplete Clustering with Optimal
  Transport
Deep Distribution-preserving Incomplete Clustering with Optimal Transport
Mingjie Luo
Siwei Wang
Xinwang Liu
Wenxuan Tu
Yi Zhang
Xifeng Guo
Sihang Zhou
En Zhu
28
0
0
21 Mar 2021
Hessian Eigenspectra of More Realistic Nonlinear Models
Hessian Eigenspectra of More Realistic Nonlinear Models
Zhenyu Liao
Michael W. Mahoney
97
31
0
02 Mar 2021
Exploiting Shared Representations for Personalized Federated Learning
Exploiting Shared Representations for Personalized Federated Learning
Liam Collins
Hamed Hassani
Aryan Mokhtari
Sanjay Shakkottai
FedMLOOD
105
736
0
14 Feb 2021
Federated Reconstruction: Partially Local Federated Learning
Federated Reconstruction: Partially Local Federated Learning
K. Singhal
Hakim Sidahmed
Zachary Garrett
Shanshan Wu
Keith Rush
Sushant Prakash
FedML
104
143
0
05 Feb 2021
Exact Linear Convergence Rate Analysis for Low-Rank Symmetric Matrix
  Completion via Gradient Descent
Exact Linear Convergence Rate Analysis for Low-Rank Symmetric Matrix Completion via Gradient Descent
Trung Vu
Raviv Raich
71
10
0
04 Feb 2021
Riemannian Perspective on Matrix Factorization
Riemannian Perspective on Matrix Factorization
Kwangjun Ahn
Felipe Suarez
49
13
0
01 Feb 2021
Low Rank Forecasting
Low Rank Forecasting
Shane T. Barratt
Yining Dong
Stephen P. Boyd
AI4TS
52
5
0
29 Jan 2021
On the computational and statistical complexity of over-parameterized
  matrix sensing
On the computational and statistical complexity of over-parameterized matrix sensing
Jiacheng Zhuo
Jeongyeol Kwon
Nhat Ho
Constantine Caramanis
141
28
0
27 Jan 2021
Beyond Procrustes: Balancing-Free Gradient Descent for Asymmetric
  Low-Rank Matrix Sensing
Beyond Procrustes: Balancing-Free Gradient Descent for Asymmetric Low-Rank Matrix Sensing
Cong Ma
Yuanxin Li
Yuejie Chi
48
3
0
13 Jan 2021
On Stochastic Variance Reduced Gradient Method for Semidefinite
  Optimization
On Stochastic Variance Reduced Gradient Method for Semidefinite Optimization
Jinshan Zeng
Yixuan Zha
Ke Ma
Yuan Yao
127
0
0
01 Jan 2021
Unbiased Subdata Selection for Fair Classification: A Unified Framework
  and Scalable Algorithms
Unbiased Subdata Selection for Fair Classification: A Unified Framework and Scalable Algorithms
Qing Ye
Weijun Xie
FaML
65
13
0
22 Dec 2020
Spectral Methods for Data Science: A Statistical Perspective
Spectral Methods for Data Science: A Statistical Perspective
Yuxin Chen
Yuejie Chi
Jianqing Fan
Cong Ma
163
173
0
15 Dec 2020
Recent Theoretical Advances in Non-Convex Optimization
Recent Theoretical Advances in Non-Convex Optimization
Marina Danilova
Pavel Dvurechensky
Alexander Gasnikov
Eduard A. Gorbunov
Sergey Guminov
Dmitry Kamzolov
Innokentiy Shibaev
129
79
0
11 Dec 2020
Recursive Importance Sketching for Rank Constrained Least Squares:
  Algorithms and High-order Convergence
Recursive Importance Sketching for Rank Constrained Least Squares: Algorithms and High-order Convergence
Yuetian Luo
Wen Huang
Xudong Li
Anru R. Zhang
76
16
0
17 Nov 2020
A Nonconvex Framework for Structured Dynamic Covariance Recovery
A Nonconvex Framework for Structured Dynamic Covariance Recovery
Katherine Tsai
Mladen Kolar
Oluwasanmi Koyejo
62
3
0
11 Nov 2020
Low-Rank Matrix Recovery with Scaled Subgradient Methods: Fast and
  Robust Convergence Without the Condition Number
Low-Rank Matrix Recovery with Scaled Subgradient Methods: Fast and Robust Convergence Without the Condition Number
Tian Tong
Cong Ma
Yuejie Chi
105
56
0
26 Oct 2020
Fast signal recovery from quadratic measurements
Fast signal recovery from quadratic measurements
Miguel Moscoso
A. Novikov
George Papanicolaou
C. Tsogka
20
1
0
11 Oct 2020
Randomized Value Functions via Posterior State-Abstraction Sampling
Randomized Value Functions via Posterior State-Abstraction Sampling
Dilip Arumugam
Benjamin Van Roy
OffRL
85
7
0
05 Oct 2020
Learning Mixtures of Low-Rank Models
Learning Mixtures of Low-Rank Models
Yanxi Chen
Cong Ma
H. Vincent Poor
Yuxin Chen
57
13
0
23 Sep 2020
Mixed-Projection Conic Optimization: A New Paradigm for Modeling Rank
  Constraints
Mixed-Projection Conic Optimization: A New Paradigm for Modeling Rank Constraints
Dimitris Bertsimas
Ryan Cory-Wright
J. Pauphilet
102
20
0
22 Sep 2020
Statistical Query Algorithms and Low-Degree Tests Are Almost Equivalent
Statistical Query Algorithms and Low-Degree Tests Are Almost Equivalent
Matthew Brennan
Guy Bresler
Samuel B. Hopkins
Jingkai Li
T. Schramm
93
66
0
13 Sep 2020
Meta-learning based Alternating Minimization Algorithm for Non-convex
  Optimization
Meta-learning based Alternating Minimization Algorithm for Non-convex Optimization
Jingyuan Xia
Shengxi Li
Jun-Jie Huang
I. Jaimoukha
Deniz Gündüz
66
72
0
09 Sep 2020
Column $\ell_{2,0}$-norm regularized factorization model of low-rank
  matrix recovery and its computation
Column ℓ2,0\ell_{2,0}ℓ2,0​-norm regularized factorization model of low-rank matrix recovery and its computation
Ting Tao
Yitian Qian
S. Pan
51
2
0
24 Aug 2020
Asymptotic Convergence Rate of Alternating Minimization for Rank One
  Matrix Completion
Asymptotic Convergence Rate of Alternating Minimization for Rank One Matrix Completion
Rui Liu
Alexander Olshevsky
47
0
0
11 Aug 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
94
16
0
04 Aug 2020
Non-Convex Structured Phase Retrieval
Non-Convex Structured Phase Retrieval
Namrata Vaswani
58
15
0
23 Jun 2020
Short-Term Traffic Forecasting Using High-Resolution Traffic Data
Short-Term Traffic Forecasting Using High-Resolution Traffic Data
Wenqing Li
Chuhan Yang
Saif Eddin Jabari
AI4TS
54
5
0
22 Jun 2020
Uncertainty quantification for nonconvex tensor completion: Confidence
  intervals, heteroscedasticity and optimality
Uncertainty quantification for nonconvex tensor completion: Confidence intervals, heteroscedasticity and optimality
Changxiao Cai
H. Vincent Poor
Yuxin Chen
118
23
0
15 Jun 2020
How Many Samples is a Good Initial Point Worth in Low-rank Matrix
  Recovery?
How Many Samples is a Good Initial Point Worth in Low-rank Matrix Recovery?
G. Zhang
Richard Y. Zhang
83
16
0
12 Jun 2020
Interpretable, similarity-driven multi-view embeddings from
  high-dimensional biomedical data
Interpretable, similarity-driven multi-view embeddings from high-dimensional biomedical data
Brian B. Avants
Nicholas J. Tustison
J. Stone
38
18
0
11 Jun 2020
A General Framework for Analyzing Stochastic Dynamics in Learning
  Algorithms
A General Framework for Analyzing Stochastic Dynamics in Learning Algorithms
Chi-Ning Chou
Juspreet Singh Sandhu
Mien Brabeeba Wang
Tiancheng Yu
64
4
0
11 Jun 2020
On Low Rank Directed Acyclic Graphs and Causal Structure Learning
On Low Rank Directed Acyclic Graphs and Causal Structure Learning
Zhuangyan Fang
Shengyu Zhu
Jiji Zhang
Yue Liu
Zhitang Chen
Yangbo He
CML
89
28
0
10 Jun 2020
MC2G: An Efficient Algorithm for Matrix Completion with Social and Item
  Similarity Graphs
MC2G: An Efficient Algorithm for Matrix Completion with Social and Item Similarity Graphs
Q. Zhang
Geewon Suh
Changho Suh
Vincent Y. F. Tan
55
15
0
08 Jun 2020
An Efficient Framework for Clustered Federated Learning
An Efficient Framework for Clustered Federated Learning
Avishek Ghosh
Jichan Chung
Dong Yin
Kannan Ramchandran
FedML
122
875
0
07 Jun 2020
Tensor Completion Made Practical
Tensor Completion Made Practical
Allen Liu
Ankur Moitra
68
33
0
04 Jun 2020
Robust Matrix Completion with Mixed Data Types
Robust Matrix Completion with Mixed Data Types
Daqian Sun
M. Wells
45
0
0
25 May 2020
Dynamic Knowledge embedding and tracing
Dynamic Knowledge embedding and tracing
Liangbei Xu
Mark A. Davenport
71
9
0
18 May 2020
Accelerating Ill-Conditioned Low-Rank Matrix Estimation via Scaled
  Gradient Descent
Accelerating Ill-Conditioned Low-Rank Matrix Estimation via Scaled Gradient Descent
Tian Tong
Cong Ma
Yuejie Chi
115
120
0
18 May 2020
Low-rank matrix completion theory via Plucker coordinates
Low-rank matrix completion theory via Plucker coordinates
M. Tsakiris
75
11
0
26 Apr 2020
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