No Spurious Local Minima in Nonconvex Low Rank Problems: A Unified Geometric Analysis

3 April 2017

Papers citing "No Spurious Local Minima in Nonconvex Low Rank Problems: A Unified Geometric Analysis"

50 / 220 papers shown

Title
Improved Global Guarantees for the Nonconvex Burer--Monteiro Factorization via Rank Overparameterization Richard Y. Zhang 30 24 0 05 Jul 2022
Preconditioned Gradient Descent for Overparameterized Nonconvex Burer--Monteiro Factorization with Global Optimality Certification G. Zhang S. Fattahi Richard Y. Zhang 62 23 0 07 Jun 2022
First-Order Algorithms for Min-Max Optimization in Geodesic Metric Spaces Michael I. Jordan Tianyi Lin Emmanouil-Vasileios Vlatakis-Gkaragkounis 29 19 0 04 Jun 2022
MetaNOR: A Meta-Learnt Nonlocal Operator Regression Approach for Metamaterial Modeling Lu Zhang Huaiqian You Yue Yu OffRL 27 7 0 04 Jun 2022
Accelerating nuclear-norm regularized low-rank matrix optimization through Burer-Monteiro decomposition Ching-pei Lee Ling Liang Tianyun Tang Kim-Chuan Toh 27 11 0 29 Apr 2022
Signal Recovery with Non-Expansive Generative Network Priors Jorio Cocola 21 1 0 24 Apr 2022
Continual learning: a feature extraction formalization, an efficient algorithm, and fundamental obstructions Binghui Peng Andrej Risteski CLL OOD 27 10 0 27 Mar 2022
Noisy Low-rank Matrix Optimization: Geometry of Local Minima and Convergence Rate Ziye Ma Somayeh Sojoudi 41 6 0 08 Mar 2022
Flat minima generalize for low-rank matrix recovery Lijun Ding Dmitriy Drusvyatskiy Maryam Fazel Zaid Harchaoui 46 16 0 07 Mar 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 30 99 0 02 Mar 2022
An Oracle Gradient Regularized Newton Method for Quadratic Measurements Regression Jun Fan Jie Sun Ailing Yan Shenglong Zhou 22 2 0 19 Feb 2022
Noise Regularizes Over-parameterized Rank One Matrix Recovery, Provably Tianyi Liu Yan Li Enlu Zhou Tuo Zhao 38 1 0 07 Feb 2022
Learning Proximal Operators to Discover Multiple Optima Lingxiao Li Noam Aigerman Vladimir G. Kim Jiajin Li Kristjan Greenewald Mikhail Yurochkin Justin Solomon 47 1 0 28 Jan 2022
Low-Pass Filtering SGD for Recovering Flat Optima in the Deep Learning Optimization Landscape Devansh Bisla Jing Wang A. Choromańska 25 34 0 20 Jan 2022
Joint Learning-Based Stabilization of Multiple Unknown Linear Systems Mohamad Kazem Shirani Faradonbeh Aditya Modi 16 6 0 01 Jan 2022
Joint Learning of Linear Time-Invariant Dynamical Systems Aditya Modi Mohamad Kazem Shirani Faradonbeh Ambuj Tewari George Michailidis 27 17 0 21 Dec 2021
Escape saddle points by a simple gradient-descent based algorithm Chenyi Zhang Tongyang Li ODL 31 15 0 28 Nov 2021
On Recovering the Best Rank-r Approximation from Few Entries Shun Xu M. Yuan 11 0 0 11 Nov 2021
On the Second-order Convergence Properties of Random Search Methods Aurelien Lucchi Antonio Orvieto Adamos Solomou 16 8 0 25 Oct 2021
Faster Perturbed Stochastic Gradient Methods for Finding Local Minima Zixiang Chen Dongruo Zhou Quanquan Gu 43 1 0 25 Oct 2021
Factorization Approach for Low-complexity Matrix Completion Problems: Exponential Number of Spurious Solutions and Failure of Gradient Methods Baturalp Yalcin Haixiang Zhang Javad Lavaei Somayeh Sojoudi 31 13 0 19 Oct 2021
Large Learning Rate Tames Homogeneity: Convergence and Balancing Effect Yuqing Wang Minshuo Chen T. Zhao Molei Tao AI4CE 57 40 0 07 Oct 2021
Provable Low Rank Plus Sparse Matrix Separation Via Nonconvex Regularizers April Sagan J. Mitchell 24 0 0 26 Sep 2021
Rank Overspecified Robust Matrix Recovery: Subgradient Method and Exact Recovery Lijun Ding Liwei Jiang Yudong Chen Qing Qu Zhihui Zhu 31 29 0 23 Sep 2021
Robust Generalization of Quadratic Neural Networks via Function Identification Kan Xu Hamsa Bastani Osbert Bastani OOD 34 8 0 22 Sep 2021
Constants of Motion: The Antidote to Chaos in Optimization and Game Dynamics Georgios Piliouras Xiao Wang 34 0 0 08 Sep 2021
Active manifolds, stratifications, and convergence to local minima in nonsmooth optimization Damek Davis Dmitriy Drusvyatskiy L. Jiang 30 10 0 26 Aug 2021
Nonconvex Factorization and Manifold Formulations are Almost Equivalent in Low-rank Matrix Optimization Yuetian Luo Xudong Li Anru R. Zhang 33 9 0 03 Aug 2021
Wave-Informed Matrix Factorization with Global Optimality Guarantees Harsha Vardhan Tetali J. Harley B. Haeffele 25 1 0 19 Jul 2021
Sparse GCA and Thresholded Gradient Descent Sheng Gao Zongming Ma 19 8 0 01 Jul 2021
Global Convergence of Gradient Descent for Asymmetric Low-Rank Matrix Factorization Tian-Chun Ye S. Du 21 46 0 27 Jun 2021
GNMR: A provable one-line algorithm for low rank matrix recovery Pini Zilber B. Nadler 48 14 0 24 Jun 2021
Escaping strict saddle points of the Moreau envelope in nonsmooth optimization Damek Davis Mateo Díaz Dmitriy Drusvyatskiy 18 14 0 17 Jun 2021
Square Root Principal Component Pursuit: Tuning-Free Noisy Robust Matrix Recovery Junhui Zhang Jingkai Yan John N. Wright 33 6 0 17 Jun 2021
Towards Understanding Generalization via Decomposing Excess Risk Dynamics Jiaye Teng Jianhao Ma Yang Yuan 29 4 0 11 Jun 2021
Rank-one matrix estimation: analytic time evolution of gradient descent dynamics A. Bodin N. Macris 17 5 0 25 May 2021
Multi-source Learning via Completion of Block-wise Overlapping Noisy Matrices D. Zhou Tianxi Cai Junwei Lu 63 9 0 21 May 2021
Lecture notes on non-convex algorithms for low-rank matrix recovery Irène Waldspurger 22 1 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 29 14 0 18 May 2021
A Geometric Analysis of Neural Collapse with Unconstrained Features Zhihui Zhu Tianyu Ding Jinxin Zhou Xiao Li Chong You Jeremias Sulam Qing Qu 33 194 0 06 May 2021
Sharp Global Guarantees for Nonconvex Low-rank Recovery in the Noisy Overparameterized Regime Richard Y. Zhang 47 25 0 21 Apr 2021
Group-Sparse Matrix Factorization for Transfer Learning of Word Embeddings Kan Xu Xuanyi Zhao Hamsa Bastani Osbert Bastani 33 6 0 18 Apr 2021
NeuSE: A Neural Snapshot Ensemble Method for Collaborative Filtering Dongsheng Li Haodong Liu Chao Chen Yingying Zhao Stephen M. Chu Bo Yang FedML 31 5 0 15 Apr 2021
Fast quantum state reconstruction via accelerated non-convex programming J. Kim G. Kollias A. Kalev K. X. Wei Anastasios Kyrillidis 33 14 0 14 Apr 2021
Escaping Saddle Points in Distributed Newton's Method with Communication Efficiency and Byzantine Resilience Avishek Ghosh R. Maity A. Mazumdar Kannan Ramchandran FedML 14 5 0 17 Mar 2021
Noisy Gradient Descent Converges to Flat Minima for Nonconvex Matrix Factorization Tianyi Liu Yan Li S. Wei Enlu Zhou T. Zhao 21 13 0 24 Feb 2021
WGAN with an Infinitely Wide Generator Has No Spurious Stationary Points Albert No Taeho Yoon Sehyun Kwon Ernest K. Ryu GAN 27 2 0 15 Feb 2021
Provable Model-based Nonlinear Bandit and Reinforcement Learning: Shelve Optimism, Embrace Virtual Curvature Kefan Dong Jiaqi Yang Tengyu Ma 24 32 0 08 Feb 2021
Escaping Saddle Points for Nonsmooth Weakly Convex Functions via Perturbed Proximal Algorithms Minhui Huang 19 6 0 04 Feb 2021
Riemannian Perspective on Matrix Factorization Kwangjun Ahn Felipe Suarez 16 13 0 01 Feb 2021