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2203.02839
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Algorithmic Regularization in Model-free Overparametrized Asymmetric Matrix Factorization
SIAM Journal on Mathematics of Data Science (SIMODS), 2022
6 March 2022
Liwei Jiang
Yudong Chen
Lijun Ding
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Papers citing
"Algorithmic Regularization in Model-free Overparametrized Asymmetric Matrix Factorization"
24 / 24 papers shown
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Preconditioned Gradient Descent for Over-Parameterized Nonconvex Matrix Factorization
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Theoretical Guarantees for Low-Rank Compression of Deep Neural Networks
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On the Crucial Role of Initialization for Matrix Factorization
International Conference on Learning Representations (ICLR), 2024
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24 Oct 2024
Robust Low-rank Tensor Train Recovery
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Provable Acceleration of Nesterov's Accelerated Gradient for Rectangular Matrix Factorization and Linear Neural Networks
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12 Oct 2024
In-depth Analysis of Low-rank Matrix Factorisation in a Federated Setting
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Federated Representation Learning in the Under-Parameterized Regime
International Conference on Machine Learning (ICML), 2024
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Cong Shen
Jing Yang
435
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07 Jun 2024
Connectivity Shapes Implicit Regularization in Matrix Factorization Models for Matrix Completion
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Jiajie Zhao
Yaoyu Zhang
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22 May 2024
The Implicit Bias of Heterogeneity towards Invariance: A Study of Multi-Environment Matrix Sensing
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Guaranteed Nonconvex Factorization Approach for Tensor Train Recovery
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Efficient Compression of Overparameterized Deep Models through Low-Dimensional Learning Dynamics
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Dogyoon Song
Laura Balzano
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354
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0
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How Over-Parameterization Slows Down Gradient Descent in Matrix Sensing: The Curses of Symmetry and Initialization
International Conference on Learning Representations (ICLR), 2023
Nuoya Xiong
Lijun Ding
Simon S. Du
549
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03 Oct 2023
Implicit Regularization Makes Overparameterized Asymmetric Matrix Sensing Robust to Perturbations
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04 Sep 2023
Gradient descent in matrix factorization: Understanding large initialization
Conference on Uncertainty in Artificial Intelligence (UAI), 2023
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Xin Chen
Mohamad Elmasri
Qiang Sun
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30 May 2023
Fast and Accurate Estimation of Low-Rank Matrices from Noisy Measurements via Preconditioned Non-Convex Gradient Descent
International Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Jialun Zhang
Hong-Ming Chiu
Richard Y. Zhang
429
8
0
26 May 2023
Convergence of Alternating Gradient Descent for Matrix Factorization
Neural Information Processing Systems (NeurIPS), 2023
R. Ward
T. Kolda
289
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11 May 2023
Saddle-to-Saddle Dynamics in Diagonal Linear Networks
Neural Information Processing Systems (NeurIPS), 2023
Scott Pesme
Nicolas Flammarion
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02 Apr 2023
Active Self-Supervised Learning: A Few Low-Cost Relationships Are All You Need
IEEE International Conference on Computer Vision (ICCV), 2023
Vivien A. Cabannes
Léon Bottou
Yann LeCun
Randall Balestriero
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0
27 Mar 2023
The Power of Preconditioning in Overparameterized Low-Rank Matrix Sensing
International Conference on Machine Learning (ICML), 2023
Xingyu Xu
Yandi Shen
Yuejie Chi
Cong Ma
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02 Feb 2023
Understanding Incremental Learning of Gradient Descent: A Fine-grained Analysis of Matrix Sensing
International Conference on Machine Learning (ICML), 2023
Jikai Jin
Zhiyuan Li
Kaifeng Lyu
S. Du
Jason D. Lee
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355
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27 Jan 2023
A Validation Approach to Over-parameterized Matrix and Image Recovery
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Zhen Qin
Liwei Jiang
Jinxin Zhou
Zhihui Zhu
485
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Tensor-on-Tensor Regression: Riemannian Optimization, Over-parameterization, Statistical-computational Gap, and Their Interplay
Annals of Statistics (Ann. Stat.), 2022
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Anru R. Zhang
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Randomly Initialized Alternating Least Squares: Fast Convergence for Matrix Sensing
SIAM Journal on Mathematics of Data Science (SIMODS), 2022
Kiryung Lee
Dominik Stöger
251
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25 Apr 2022
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