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
On the computational and statistical complexity of over-parameterized matrix sensing Jiacheng Zhuo Jeongyeol Kwon Nhat Ho C. Caramanis 27 28 0 27 Jan 2021
Beyond Procrustes: Balancing-Free Gradient Descent for Asymmetric Low-Rank Matrix Sensing Cong Ma Yuanxin Li Yuejie Chi 21 3 0 13 Jan 2021
HePPCAT: Probabilistic PCA for Data with Heteroscedastic Noise David Hong Kyle Gilman Laura Balzano Jeffrey A. Fessler 40 19 0 10 Jan 2021
Fast Global Convergence for Low-rank Matrix Recovery via Riemannian Gradient Descent with Random Initialization T. Hou Zhenzhen Li Ziyun Zhang 23 18 0 31 Dec 2020
Stochastic Approximation for Online Tensorial Independent Component Analysis C. J. Li Michael I. Jordan 30 2 0 28 Dec 2020
Rank-One Measurements of Low-Rank PSD Matrices Have Small Feasible Sets T. Roddenberry Santiago Segarra Anastasios Kyrillidis 21 0 0 17 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
On The Convergence of First Order Methods for Quasar-Convex Optimization Jikai Jin 24 9 0 10 Oct 2020
Learning Mixtures of Low-Rank Models Yanxi Chen Cong Ma H. Vincent Poor Yuxin Chen 26 13 0 23 Sep 2020
Low-rank matrix recovery with non-quadratic loss: projected gradient method and regularity projection oracle Lijun Ding Yuqian Zhang Yudong Chen 16 1 0 31 Aug 2020
$Column $\ell_{2,0}$-norm regularized factorization model of low-rank matrix recovery and its computation$ Column $\ell_{2,0}$ -norm regularized factorization model of low-rank matrix recovery and its computation Ting Tao Yitian Qian S. Pan 40 2 0 24 Aug 2020
Notes on Worst-case Inefficiency of Gradient Descent Even in R^2 Shiliang Zuo 9 0 0 17 Aug 2020
From Symmetry to Geometry: Tractable Nonconvex Problems Yuqian Zhang Qing Qu John N. Wright 34 43 0 14 Jul 2020
Differentiable Programming for Hyperspectral Unmixing using a Physics-based Dispersion Model J. Janiczek Parth Thaker Gautam Dasarathy C. Edwards P. Christensen Suren Jayasuriya 29 3 0 12 Jul 2020
Optimization Landscape of Tucker Decomposition Abraham Frandsen Rong Ge 17 14 0 29 Jun 2020
Accelerating Ill-Conditioned Low-Rank Matrix Estimation via Scaled Gradient Descent Tian Tong Cong Ma Yuejie Chi 27 115 0 18 May 2020
Escaping Saddle Points Efficiently with Occupation-Time-Adapted Perturbations Xin Guo Jiequn Han Mahan Tajrobehkar Wenpin Tang 19 2 0 09 May 2020
Second-Order Guarantees in Centralized, Federated and Decentralized Nonconvex Optimization Stefan Vlaski Ali H. Sayed 23 5 0 31 Mar 2020
Nonconvex Matrix Completion with Linearly Parameterized Factors Ji Chen Xiaodong Li Zongming Ma 16 3 0 29 Mar 2020
The Landscape of Matrix Factorization Revisited Hossein Valavi Sulin Liu Peter J. Ramadge 17 5 0 27 Feb 2020
Provable Meta-Learning of Linear Representations Nilesh Tripuraneni Chi Jin Michael I. Jordan OOD 19 188 0 26 Feb 2020
Recommendation on a Budget: Column Space Recovery from Partially Observed Entries with Random or Active Sampling Carolyn Kim Mohsen Bayati 23 0 0 26 Feb 2020
Fast Convergence for Langevin Diffusion with Manifold Structure Ankur Moitra Andrej Risteski 19 7 0 13 Feb 2020
On the Sample Complexity and Optimization Landscape for Quadratic Feasibility Problems Parth Thaker Gautam Dasarathy Angelia Nedić 24 5 0 04 Feb 2020
Replica Exchange for Non-Convex Optimization Jing-rong Dong Xin T. Tong 27 21 0 23 Jan 2020
Thresholds of descending algorithms in inference problems Stefano Sarao Mannelli Lenka Zdeborova AI4CE 24 4 0 02 Jan 2020
Avoiding Spurious Local Minima in Deep Quadratic Networks A. Kazemipour Brett W. Larsen S. Druckmann ODL 25 6 0 31 Dec 2019
Revisiting Landscape Analysis in Deep Neural Networks: Eliminating Decreasing Paths to Infinity Shiyu Liang Ruoyu Sun R. Srikant 35 19 0 31 Dec 2019
Landscape Connectivity and Dropout Stability of SGD Solutions for Over-parameterized Neural Networks A. Shevchenko Marco Mondelli 27 37 0 20 Dec 2019
Proximal methods avoid active strict saddles of weakly convex functions Damek Davis Dmitriy Drusvyatskiy 10 3 0 16 Dec 2019
Polynomial time guarantees for the Burer-Monteiro method Diego Cifuentes Ankur Moitra 23 36 0 03 Dec 2019
Manifold Gradient Descent Solves Multi-Channel Sparse Blind Deconvolution Provably and Efficiently Laixi Shi Yuejie Chi 30 26 0 25 Nov 2019
Communication-Efficient and Byzantine-Robust Distributed Learning with Error Feedback Avishek Ghosh R. Maity S. Kadhe A. Mazumdar Kannan Ramchandran FedML 21 27 0 21 Nov 2019
Implicit Regularization and Convergence for Weight Normalization Xiaoxia Wu Yan Sun Tongzheng Ren Shanshan Wu Zhiyuan Li Suriya Gunasekar Rachel A. Ward Qiang Liu 20 21 0 18 Nov 2019
Error bound of critical points and KL property of exponent $1/2$ for squared F-norm regularized factorization Ting Tao S. Pan Shujun Bi 25 4 0 11 Nov 2019
Linear Speedup in Saddle-Point Escape for Decentralized Non-Convex Optimization Stefan Vlaski Ali H. Sayed 28 2 0 30 Oct 2019
Mildly Overparametrized Neural Nets can Memorize Training Data Efficiently Rong Ge Runzhe Wang Haoyu Zhao TDI 18 20 0 26 Sep 2019
$KL property of exponent $1/2$ of $\ell_{2,0}$-norm and DC regularized factorizations for low-rank matrix recovery$ KL property of exponent $1/2$ of $\ell_{2,0}$ -norm and DC regularized factorizations for low-rank matrix recovery Shujun Bi Ting Tao S. Pan 23 1 0 24 Aug 2019
Extending the step-size restriction for gradient descent to avoid strict saddle points Hayden Schaeffer S. McCalla 18 4 0 05 Aug 2019
Who is Afraid of Big Bad Minima? Analysis of Gradient-Flow in a Spiked Matrix-Tensor Model Stefano Sarao Mannelli Giulio Biroli C. Cammarota Florent Krzakala Lenka Zdeborová 25 41 0 18 Jul 2019
The Landscape of Non-convex Empirical Risk with Degenerate Population Risk Shuang Li Gongguo Tang M. Wakin MedIm 26 7 0 11 Jul 2019
SNAP: Finding Approximate Second-Order Stationary Solutions Efficiently for Non-convex Linearly Constrained Problems Songtao Lu Meisam Razaviyayn Bo Yang Kejun Huang Mingyi Hong 27 11 0 09 Jul 2019
Limitations of Lazy Training of Two-layers Neural Networks Behrooz Ghorbani Song Mei Theodor Misiakiewicz Andrea Montanari MLT 16 143 0 21 Jun 2019
Implicit Regularization in Deep Matrix Factorization Sanjeev Arora Nadav Cohen Wei Hu Yuping Luo AI4CE 38 491 0 31 May 2019
Collaborative Self-Attention for Recommender Systems Kai-Lang Yao Wu-Jun Li 30 1 0 27 May 2019
Leader Stochastic Gradient Descent for Distributed Training of Deep Learning Models: Extension Yunfei Teng Wenbo Gao F. Chalus A. Choromańska D. Goldfarb Adrian Weller 27 12 0 24 May 2019
High dimensional VAR with low rank transition Pierre Alquier Karine Bertin P. Doukhan Rémy Garnier BDL 21 16 0 02 May 2019
Stabilized SVRG: Simple Variance Reduction for Nonconvex Optimization Rong Ge Zhize Li Weiyao Wang Xiang Wang 19 33 0 01 May 2019
On Stationary-Point Hitting Time and Ergodicity of Stochastic Gradient Langevin Dynamics Xi Chen S. Du Xin T. Tong 28 33 0 30 Apr 2019
Low-rank matrix recovery with composite optimization: good conditioning and rapid convergence Vasileios Charisopoulos Yudong Chen Damek Davis Mateo Díaz Lijun Ding Dmitriy Drusvyatskiy 14 83 0 22 Apr 2019