Global Optimality of Local Search for Low Rank Matrix Recovery

23 May 2016

Srinadh Bhojanapalli

Papers citing "Global Optimality of Local Search for Low Rank Matrix Recovery"

50 / 60 papers shown

Title
Preconditioned Gradient Descent for Over-Parameterized Nonconvex Matrix Factorization G. Zhang S. Fattahi Richard Y. Zhang 40 34 0 13 Apr 2025
Compressible Dynamics in Deep Overparameterized Low-Rank Learning & Adaptation Can Yaras Peng Wang Laura Balzano Qing Qu AI4CE 37 12 0 06 Jun 2024
Wave Physics-informed Matrix Factorizations Harsha Vardhan Tetali J. Harley B. Haeffele 32 0 0 21 Dec 2023
Provably Accelerating Ill-Conditioned Low-rank Estimation via Scaled Gradient Descent, Even with Overparameterization Cong Ma Xingyu Xu Tian Tong Yuejie Chi 18 9 0 09 Oct 2023
Saddle-to-Saddle Dynamics in Diagonal Linear Networks Scott Pesme Nicolas Flammarion 31 35 0 02 Apr 2023
A Newton-CG based barrier-augmented Lagrangian method for general nonconvex conic optimization Chuan He Heng Huang Zhaosong Lu 14 1 0 10 Jan 2023
Escaping From Saddle Points Using Asynchronous Coordinate Gradient Descent Marco Bornstein Jin-Peng Liu Jingling Li Furong Huang 21 0 0 17 Nov 2022
Are All Losses Created Equal: A Neural Collapse Perspective Jinxin Zhou Chong You Xiao Li Kangning Liu Sheng Liu Qing Qu Zhihui Zhu 36 58 0 04 Oct 2022
Nonconvex Matrix Factorization is Geodesically Convex: Global Landscape Analysis for Fixed-rank Matrix Optimization From a Riemannian Perspective Yuetian Luo Nicolas García Trillos 19 6 0 29 Sep 2022
A Validation Approach to Over-parameterized Matrix and Image Recovery Lijun Ding Zhen Qin Liwei Jiang Jinxin Zhou Zhihui Zhu 45 13 0 21 Sep 2022
Gradient-Free Methods for Deterministic and Stochastic Nonsmooth Nonconvex Optimization Tianyi Lin Zeyu Zheng Michael I. Jordan 51 51 0 12 Sep 2022
Implicit Full Waveform Inversion with Deep Neural Representation Jian Sun K. Innanen AI4CE 37 32 0 08 Sep 2022
Accelerating SGD for Highly Ill-Conditioned Huge-Scale Online Matrix Completion G. Zhang Hong-Ming Chiu Richard Y. Zhang 16 10 0 24 Aug 2022
Blessing of Nonconvexity in Deep Linear Models: Depth Flattens the Optimization Landscape Around the True Solution Jianhao Ma S. Fattahi 42 5 0 15 Jul 2022
$Intrinsic dimensionality and generalization properties of the $\mathcal{R}$-norm inductive bias$ Intrinsic dimensionality and generalization properties of the $\mathcal{R}$ -norm inductive bias Navid Ardeshir Daniel J. Hsu Clayton Sanford CML AI4CE 18 6 0 10 Jun 2022
Preconditioned Gradient Descent for Overparameterized Nonconvex Burer--Monteiro Factorization with Global Optimality Certification G. Zhang S. Fattahi Richard Y. Zhang 42 23 0 07 Jun 2022
Randomly Initialized Alternating Least Squares: Fast Convergence for Matrix Sensing Kiryung Lee Dominik Stöger 25 11 0 25 Apr 2022
On the Optimization Landscape of Neural Collapse under MSE Loss: Global Optimality with Unconstrained Features Jinxin Zhou Xiao Li Tian Ding Chong You Qing Qu Zhihui Zhu 24 97 0 02 Mar 2022
Escape saddle points by a simple gradient-descent based algorithm Chenyi Zhang Tongyang Li ODL 23 15 0 28 Nov 2021
Faster Perturbed Stochastic Gradient Methods for Finding Local Minima Zixiang Chen Dongruo Zhou Quanquan Gu 35 1 0 25 Oct 2021
Nonconvex Factorization and Manifold Formulations are Almost Equivalent in Low-rank Matrix Optimization Yuetian Luo Xudong Li Anru R. Zhang 25 9 0 03 Aug 2021
Small random initialization is akin to spectral learning: Optimization and generalization guarantees for overparameterized low-rank matrix reconstruction Dominik Stöger Mahdi Soltanolkotabi ODL 42 75 0 28 Jun 2021
Escaping Saddle Points with Compressed SGD Dmitrii Avdiukhin G. Yaroslavtsev 8 4 0 21 May 2021
Sharp Restricted Isometry Property Bounds for Low-rank Matrix Recovery Problems with Corrupted Measurements Ziye Ma Yingjie Bi Javad Lavaei Somayeh Sojoudi 21 14 0 18 May 2021
Sharp Global Guarantees for Nonconvex Low-rank Recovery in the Noisy Overparameterized Regime Richard Y. Zhang 39 1 0 21 Apr 2021
Group-Sparse Matrix Factorization for Transfer Learning of Word Embeddings Kan Xu Xuanyi Zhao Hamsa Bastani Osbert Bastani 25 6 0 18 Apr 2021
Generalized Low-rank plus Sparse Tensor Estimation by Fast Riemannian Optimization Jian-Feng Cai Jingyang Li Dong Xia 49 30 0 16 Mar 2021
HePPCAT: Probabilistic PCA for Data with Heteroscedastic Noise David Hong Kyle Gilman Laura Balzano Jeffrey A. Fessler 32 18 0 10 Jan 2021
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
Accelerating Ill-Conditioned Low-Rank Matrix Estimation via Scaled Gradient Descent Tian Tong Cong Ma Yuejie Chi 19 113 0 18 May 2020
On the Sample Complexity and Optimization Landscape for Quadratic Feasibility Problems Parth Thaker Gautam Dasarathy Angelia Nedić 16 5 0 04 Feb 2020
Revisiting Landscape Analysis in Deep Neural Networks: Eliminating Decreasing Paths to Infinity Shiyu Liang Ruoyu Sun R. Srikant 27 19 0 31 Dec 2019
Manifold Gradient Descent Solves Multi-Channel Sparse Blind Deconvolution Provably and Efficiently Laixi Shi Yuejie Chi 22 26 0 25 Nov 2019
Global Optimality Guarantees For Policy Gradient Methods Jalaj Bhandari Daniel Russo 35 185 0 05 Jun 2019
Implicit Regularization in Deep Matrix Factorization Sanjeev Arora Nadav Cohen Wei Hu Yuping Luo AI4CE 24 491 0 31 May 2019
Stabilized SVRG: Simple Variance Reduction for Nonconvex Optimization Rong Ge Zhize Li Weiyao Wang Xiang Wang 17 33 0 01 May 2019
A Deterministic Gradient-Based Approach to Avoid Saddle Points L. Kreusser Stanley J. Osher Bao Wang ODL 24 3 0 21 Jan 2019
On the Global Convergence of Imitation Learning: A Case for Linear Quadratic Regulator Qi Cai Mingyi Hong Yongxin Chen Zhaoran Wang 19 34 0 11 Jan 2019
Convergence of Cubic Regularization for Nonconvex Optimization under KL Property Yi Zhou Zhe Wang Yingbin Liang 24 23 0 22 Aug 2018
Optimistic mirror descent in saddle-point problems: Going the extra (gradient) mile P. Mertikopoulos Bruno Lecouat Houssam Zenati Chuan-Sheng Foo V. Chandrasekhar Georgios Piliouras 19 290 0 07 Jul 2018
On the Implicit Bias of Dropout Poorya Mianjy R. Arora René Vidal 27 66 0 26 Jun 2018
Stochastic Nested Variance Reduction for Nonconvex Optimization Dongruo Zhou Pan Xu Quanquan Gu 25 146 0 20 Jun 2018
Improved Learning of One-hidden-layer Convolutional Neural Networks with Overlaps S. Du Surbhi Goel MLT 20 17 0 20 May 2018
The Global Optimization Geometry of Shallow Linear Neural Networks Zhihui Zhu Daniel Soudry Yonina C. Eldar M. Wakin ODL 18 36 0 13 May 2018
Fast and Sample Efficient Inductive Matrix Completion via Multi-Phase Procrustes Flow Xiao Zhang S. Du Quanquan Gu 23 24 0 03 Mar 2018
Smoothed analysis for low-rank solutions to semidefinite programs in quadratic penalty form Srinadh Bhojanapalli Nicolas Boumal Prateek Jain Praneeth Netrapalli 23 42 0 01 Mar 2018
Stochastic Variance-Reduced Cubic Regularization for Nonconvex Optimization Zhe Wang Yi Zhou Yingbin Liang Guanghui Lan 35 46 0 20 Feb 2018
Spurious Local Minima are Common in Two-Layer ReLU Neural Networks Itay Safran Ohad Shamir 31 261 0 24 Dec 2017
A Distributed Frank-Wolfe Framework for Learning Low-Rank Matrices with the Trace Norm Wenjie Zheng A. Bellet Patrick Gallinari 18 19 0 20 Dec 2017
Accelerated Gradient Descent Escapes Saddle Points Faster than Gradient Descent Chi Jin Praneeth Netrapalli Michael I. Jordan ODL 29 261 0 28 Nov 2017