Global Convergence of Gradient Descent for Asymmetric Low-Rank Matrix Factorization

27 June 2021

Papers citing "Global Convergence of Gradient Descent for Asymmetric Low-Rank Matrix Factorization"

32 / 32 papers shown

Title
Stability properties of gradient flow dynamics for the symmetric low-rank matrix factorization problem Hesameddin Mohammadi Mohammad Tinati Stephen Tu Mahdi Soltanolkotabi M. Jovanović 68 0 0 24 Nov 2024
BLAST: Block-Level Adaptive Structured Matrices for Efficient Deep Neural Network Inference Changwoo Lee Soo Min Kwon Qing Qu Hun-Seok Kim 22 0 0 28 Oct 2024
On the Crucial Role of Initialization for Matrix Factorization Bingcong Li Liang Zhang Aryan Mokhtari Niao He 26 1 0 24 Oct 2024
Provable Acceleration of Nesterov's Accelerated Gradient for Rectangular Matrix Factorization and Linear Neural Networks Zhenghao Xu Yuqing Wang T. Zhao Rachel Ward Molei Tao 19 0 0 12 Oct 2024
On subdifferential chain rule of matrix factorization and beyond Jiewen Guan Anthony Man-Cho So AI4CE 16 1 0 07 Oct 2024
In-depth Analysis of Low-rank Matrix Factorisation in a Federated Setting Constantin Philippenko Kevin Scaman Laurent Massoulié FedML 29 1 0 13 Sep 2024
Federated Representation Learning in the Under-Parameterized Regime Renpu Liu Cong Shen Jing Yang 19 4 0 07 Jun 2024
Reweighted Solutions for Weighted Low Rank Approximation David P. Woodruff T. Yasuda 18 1 0 04 Jun 2024
On the Convergence of Differentially-Private Fine-tuning: To Linearly Probe or to Fully Fine-tune? Shuqi Ke Charlie Hou Giulia Fanti Sewoong Oh 34 4 0 29 Feb 2024
Good regularity creates large learning rate implicit biases: edge of stability, balancing, and catapult Yuqing Wang Zhenghao Xu Tuo Zhao Molei Tao 24 10 0 26 Oct 2023
Matrix Compression via Randomized Low Rank and Low Precision Factorization R. Saha Varun Srivastava Mert Pilanci 13 18 0 17 Oct 2023
How Over-Parameterization Slows Down Gradient Descent in Matrix Sensing: The Curses of Symmetry and Initialization Nuoya Xiong Lijun Ding Simon S. Du 14 11 0 03 Oct 2023
Asymmetric matrix sensing by gradient descent with small random initialization J. S. Wind 23 1 0 04 Sep 2023
Maestro: Uncovering Low-Rank Structures via Trainable Decomposition Samuel Horváth Stefanos Laskaridis Shashank Rajput Hongyi Wang BDL 26 4 0 28 Aug 2023
Convergence of Alternating Gradient Descent for Matrix Factorization R. Ward T. Kolda 22 6 0 11 May 2023
The Ideal Continual Learner: An Agent That Never Forgets Liangzu Peng Paris V. Giampouras René Vidal CLL 106 26 0 29 Apr 2023
Active Self-Supervised Learning: A Few Low-Cost Relationships Are All You Need Vivien A. Cabannes Léon Bottou Yann LeCun Randall Balestriero 29 13 0 27 Mar 2023
Greedy Pruning with Group Lasso Provably Generalizes for Matrix Sensing Nived Rajaraman Devvrit Aryan Mokhtari Kannan Ramchandran 18 0 0 20 Mar 2023
The Power of Preconditioning in Overparameterized Low-Rank Matrix Sensing Xingyu Xu Yandi Shen Yuejie Chi Cong Ma 22 34 0 02 Feb 2023
Rank-1 Matrix Completion with Gradient Descent and Small Random Initialization Daesung Kim Hye Won Chung 17 2 0 19 Dec 2022
A Novel Stochastic Gradient Descent Algorithm for Learning Principal Subspaces Charline Le Lan Joshua Greaves Jesse Farebrother Mark Rowland Fabian Pedregosa Rishabh Agarwal Marc G. Bellemare 35 8 0 08 Dec 2022
Behind the Scenes of Gradient Descent: A Trajectory Analysis via Basis Function Decomposition Jianhao Ma Li-Zhen Guo S. Fattahi 19 4 0 01 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 9 6 0 29 Sep 2022
Accelerating nuclear-norm regularized low-rank matrix optimization through Burer-Monteiro decomposition Ching-pei Lee Ling Liang Tianyun Tang Kim-Chuan Toh 11 11 0 29 Apr 2022
Randomly Initialized Alternating Least Squares: Fast Convergence for Matrix Sensing Kiryung Lee Dominik Stöger 13 11 0 25 Apr 2022
Continual learning: a feature extraction formalization, an efficient algorithm, and fundamental obstructions Binghui Peng Andrej Risteski CLL OOD 17 10 0 27 Mar 2022
Flat minima generalize for low-rank matrix recovery Lijun Ding D. Drusvyatskiy Maryam Fazel Zaid Harchaoui 18 16 0 07 Mar 2022
Algorithmic Regularization in Model-free Overparametrized Asymmetric Matrix Factorization Liwei Jiang Yudong Chen Lijun Ding 15 26 0 06 Mar 2022
How and When Random Feedback Works: A Case Study of Low-Rank Matrix Factorization Shivam Garg Santosh Vempala 9 3 0 17 Nov 2021
Large Learning Rate Tames Homogeneity: Convergence and Balancing Effect Yuqing Wang Minshuo Chen T. Zhao Molei Tao AI4CE 55 40 0 07 Oct 2021
Nonconvex Factorization and Manifold Formulations are Almost Equivalent in Low-rank Matrix Optimization Yuetian Luo Xudong Li Anru R. Zhang 15 9 0 03 Aug 2021
GNMR: A provable one-line algorithm for low rank matrix recovery Pini Zilber B. Nadler 40 13 0 24 Jun 2021