Nonconvex Optimization Meets Low-Rank Matrix Factorization: An Overview

25 September 2018

Papers citing "Nonconvex Optimization Meets Low-Rank Matrix Factorization: An Overview"

25 / 75 papers shown

Title
HePPCAT: Probabilistic PCA for Data with Heteroscedastic Noise David Hong Kyle Gilman Laura Balzano Jeffrey A. Fessler 40 19 0 10 Jan 2021
The Nonconvex Geometry of Linear Inverse Problems Armin Eftekhari Peyman Mohajerin Esfahani 20 1 0 07 Jan 2021
Spectral Methods for Data Science: A Statistical Perspective Yuxin Chen Yuejie Chi Jianqing Fan Cong Ma 40 165 0 15 Dec 2020
Recursive Importance Sketching for Rank Constrained Least Squares: Algorithms and High-order Convergence Yuetian Luo Wen Huang Xudong Li Anru R. Zhang 23 15 0 17 Nov 2020
Low-Rank Matrix Recovery with Scaled Subgradient Methods: Fast and Robust Convergence Without the Condition Number Tian Tong Cong Ma Yuejie Chi 16 55 0 26 Oct 2020
Escaping Saddle Points in Ill-Conditioned Matrix Completion with a Scalable Second Order Method C. Kümmerle C. M. Verdun 19 6 0 07 Sep 2020
Shape Matters: Understanding the Implicit Bias of the Noise Covariance Jeff Z. HaoChen Colin Wei J. Lee Tengyu Ma 29 93 0 15 Jun 2020
An Analysis of Constant Step Size SGD in the Non-convex Regime: Asymptotic Normality and Bias Lu Yu Krishnakumar Balasubramanian S. Volgushev Murat A. Erdogdu 35 50 0 14 Jun 2020
Adversarial Classification via Distributional Robustness with Wasserstein Ambiguity Nam Ho-Nguyen Stephen J. Wright OOD 45 16 0 28 May 2020
Accelerating Ill-Conditioned Low-Rank Matrix Estimation via Scaled Gradient Descent Tian Tong Cong Ma Yuejie Chi 27 113 0 18 May 2020
Implicit Regularization in Deep Learning May Not Be Explainable by Norms Noam Razin Nadav Cohen 24 155 0 13 May 2020
An Optimal Statistical and Computational Framework for Generalized Tensor Estimation Rungang Han Rebecca Willett Anru R. Zhang 27 65 0 26 Feb 2020
$Depth Descent Synchronization in $\mathrm{SO}(D)$$ Depth Descent Synchronization in $\mathrm{SO}(D)$ Tyler Maunu Gilad Lerman MDE 34 2 0 13 Feb 2020
Rank $2r$ iterative least squares: efficient recovery of ill-conditioned low rank matrices from few entries Jonathan Bauch B. Nadler Pini Zilber 37 14 0 05 Feb 2020
Optimization for deep learning: theory and algorithms Ruoyu Sun ODL 19 168 0 19 Dec 2019
Manifold Gradient Descent Solves Multi-Channel Sparse Blind Deconvolution Provably and Efficiently Laixi Shi Yuejie Chi 30 26 0 25 Nov 2019
High-dimensional principal component analysis with heterogeneous missingness Ziwei Zhu Tengyao Wang R. Samworth 39 47 0 28 Jun 2019
Implicit Regularization in Deep Matrix Factorization Sanjeev Arora Nadav Cohen Wei Hu Yuping Luo AI4CE 29 491 0 31 May 2019
Noisy Matrix Completion: Understanding Statistical Guarantees for Convex Relaxation via Nonconvex Optimization Yuxin Chen Yuejie Chi Jianqing Fan Cong Ma Yuling Yan 17 128 0 20 Feb 2019
Subgradient Descent Learns Orthogonal Dictionaries Yu Bai Qijia Jiang Ju Sun 17 51 0 25 Oct 2018
A Survey on Nonconvex Regularization Based Sparse and Low-Rank Recovery in Signal Processing, Statistics, and Machine Learning Fei Wen L. Chu Peilin Liu Robert C. Qiu 23 153 0 16 Aug 2018
Robust high dimensional factor models with applications to statistical machine learning Jianqing Fan Kaizheng Wang Yiqiao Zhong Ziwei Zhu 32 53 0 12 Aug 2018
A modern maximum-likelihood theory for high-dimensional logistic regression Pragya Sur Emmanuel J. Candes 23 285 0 19 Mar 2018
Learning Latent Features with Pairwise Penalties in Low-Rank Matrix Completion Kaiyi Ji Jian Tan Jinfeng Xu Yuejie Chi 25 3 0 16 Feb 2018
The Projected Power Method: An Efficient Algorithm for Joint Alignment from Pairwise Differences Yuxin Chen Emmanuel Candes 37 92 0 19 Sep 2016