ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2012.09839
  4. Cited By
Towards Resolving the Implicit Bias of Gradient Descent for Matrix
  Factorization: Greedy Low-Rank Learning

Towards Resolving the Implicit Bias of Gradient Descent for Matrix Factorization: Greedy Low-Rank Learning

17 December 2020
Zhiyuan Li
Yuping Luo
Kaifeng Lyu
ArXivPDFHTML

Papers citing "Towards Resolving the Implicit Bias of Gradient Descent for Matrix Factorization: Greedy Low-Rank Learning"

41 / 41 papers shown
Title
Gradient Descent Robustly Learns the Intrinsic Dimension of Data in Training Convolutional Neural Networks
Gradient Descent Robustly Learns the Intrinsic Dimension of Data in Training Convolutional Neural Networks
Chenyang Zhang
Peifeng Gao
Difan Zou
Yuan Cao
OOD
MLT
62
0
0
11 Apr 2025
Implicit Bias in Matrix Factorization and its Explicit Realization in a New Architecture
Yikun Hou
Suvrit Sra
A. Yurtsever
34
0
0
28 Jan 2025
From Lazy to Rich: Exact Learning Dynamics in Deep Linear Networks
From Lazy to Rich: Exact Learning Dynamics in Deep Linear Networks
Clémentine Dominé
Nicolas Anguita
A. Proca
Lukas Braun
D. Kunin
P. Mediano
Andrew M. Saxe
38
3
0
22 Sep 2024
How DNNs break the Curse of Dimensionality: Compositionality and Symmetry Learning
How DNNs break the Curse of Dimensionality: Compositionality and Symmetry Learning
Arthur Jacot
Seok Hoan Choi
Yuxiao Wen
AI4CE
94
2
0
08 Jul 2024
Compressible Dynamics in Deep Overparameterized Low-Rank Learning &
  Adaptation
Compressible Dynamics in Deep Overparameterized Low-Rank Learning & Adaptation
Can Yaras
Peng Wang
Laura Balzano
Qing Qu
AI4CE
37
13
0
06 Jun 2024
Hamiltonian Mechanics of Feature Learning: Bottleneck Structure in Leaky ResNets
Hamiltonian Mechanics of Feature Learning: Bottleneck Structure in Leaky ResNets
Arthur Jacot
Alexandre Kaiser
36
0
0
27 May 2024
Connectivity Shapes Implicit Regularization in Matrix Factorization Models for Matrix Completion
Connectivity Shapes Implicit Regularization in Matrix Factorization Models for Matrix Completion
Zhiwei Bai
Jiajie Zhao
Yaoyu Zhang
AI4CE
37
0
0
22 May 2024
Early Directional Convergence in Deep Homogeneous Neural Networks for Small Initializations
Early Directional Convergence in Deep Homogeneous Neural Networks for Small Initializations
Akshay Kumar
Jarvis Haupt
ODL
44
3
0
12 Mar 2024
The Expected Loss of Preconditioned Langevin Dynamics Reveals the
  Hessian Rank
The Expected Loss of Preconditioned Langevin Dynamics Reveals the Hessian Rank
Amitay Bar
Rotem Mulayoff
T. Michaeli
Ronen Talmon
64
0
0
21 Feb 2024
Which Frequencies do CNNs Need? Emergent Bottleneck Structure in Feature Learning
Which Frequencies do CNNs Need? Emergent Bottleneck Structure in Feature Learning
Yuxiao Wen
Arthur Jacot
60
6
0
12 Feb 2024
Implicit Bias and Fast Convergence Rates for Self-attention
Implicit Bias and Fast Convergence Rates for Self-attention
Bhavya Vasudeva
Puneesh Deora
Christos Thrampoulidis
37
13
0
08 Feb 2024
How Over-Parameterization Slows Down Gradient Descent in Matrix Sensing:
  The Curses of Symmetry and Initialization
How Over-Parameterization Slows Down Gradient Descent in Matrix Sensing: The Curses of Symmetry and Initialization
Nuoya Xiong
Lijun Ding
Simon S. Du
35
11
0
03 Oct 2023
Early Neuron Alignment in Two-layer ReLU Networks with Small
  Initialization
Early Neuron Alignment in Two-layer ReLU Networks with Small Initialization
Hancheng Min
Enrique Mallada
René Vidal
MLT
34
19
0
24 Jul 2023
The Implicit Bias of Batch Normalization in Linear Models and Two-layer
  Linear Convolutional Neural Networks
The Implicit Bias of Batch Normalization in Linear Models and Two-layer Linear Convolutional Neural Networks
Yuan Cao
Difan Zou
Yuan-Fang Li
Quanquan Gu
MLT
37
5
0
20 Jun 2023
Gradient descent in matrix factorization: Understanding large
  initialization
Gradient descent in matrix factorization: Understanding large initialization
Hengchao Chen
Xin Chen
Mohamad Elmasri
Qiang Sun
AI4CE
31
1
0
30 May 2023
Robust Sparse Mean Estimation via Incremental Learning
Robust Sparse Mean Estimation via Incremental Learning
Jianhao Ma
Ruidi Chen
Yinghui He
S. Fattahi
Wei Hu
36
0
0
24 May 2023
Saddle-to-Saddle Dynamics in Diagonal Linear Networks
Saddle-to-Saddle Dynamics in Diagonal Linear Networks
Scott Pesme
Nicolas Flammarion
31
35
0
02 Apr 2023
Penalising the biases in norm regularisation enforces sparsity
Penalising the biases in norm regularisation enforces sparsity
Etienne Boursier
Nicolas Flammarion
40
14
0
02 Mar 2023
Learning time-scales in two-layers neural networks
Learning time-scales in two-layers neural networks
Raphael Berthier
Andrea Montanari
Kangjie Zhou
38
33
0
28 Feb 2023
Implicit Regularization Leads to Benign Overfitting for Sparse Linear
  Regression
Implicit Regularization Leads to Benign Overfitting for Sparse Linear Regression
Mo Zhou
Rong Ge
29
2
0
01 Feb 2023
Understanding Incremental Learning of Gradient Descent: A Fine-grained
  Analysis of Matrix Sensing
Understanding Incremental Learning of Gradient Descent: A Fine-grained Analysis of Matrix Sensing
Jikai Jin
Zhiyuan Li
Kaifeng Lyu
S. Du
Jason D. Lee
MLT
54
34
0
27 Jan 2023
Infinite-width limit of deep linear neural networks
Infinite-width limit of deep linear neural networks
Lénaïc Chizat
Maria Colombo
Xavier Fernández-Real
Alessio Figalli
31
14
0
29 Nov 2022
Same Pre-training Loss, Better Downstream: Implicit Bias Matters for
  Language Models
Same Pre-training Loss, Better Downstream: Implicit Bias Matters for Language Models
Hong Liu
Sang Michael Xie
Zhiyuan Li
Tengyu Ma
AI4CE
40
49
0
25 Oct 2022
Behind the Scenes of Gradient Descent: A Trajectory Analysis via Basis
  Function Decomposition
Behind the Scenes of Gradient Descent: A Trajectory Analysis via Basis Function Decomposition
Jianhao Ma
Li-Zhen Guo
S. Fattahi
38
4
0
01 Oct 2022
Implicit Bias of Large Depth Networks: a Notion of Rank for Nonlinear
  Functions
Implicit Bias of Large Depth Networks: a Notion of Rank for Nonlinear Functions
Arthur Jacot
36
25
0
29 Sep 2022
Deep Linear Networks can Benignly Overfit when Shallow Ones Do
Deep Linear Networks can Benignly Overfit when Shallow Ones Do
Niladri S. Chatterji
Philip M. Long
23
8
0
19 Sep 2022
On the Implicit Bias in Deep-Learning Algorithms
On the Implicit Bias in Deep-Learning Algorithms
Gal Vardi
FedML
AI4CE
34
72
0
26 Aug 2022
Implicit Regularization with Polynomial Growth in Deep Tensor
  Factorization
Implicit Regularization with Polynomial Growth in Deep Tensor Factorization
Kais Hariz
Hachem Kadri
Stéphane Ayache
Maher Moakher
Thierry Artières
26
2
0
18 Jul 2022
Blessing of Nonconvexity in Deep Linear Models: Depth Flattens the
  Optimization Landscape Around the True Solution
Blessing of Nonconvexity in Deep Linear Models: Depth Flattens the Optimization Landscape Around the True Solution
Jianhao Ma
S. Fattahi
44
5
0
15 Jul 2022
Implicit Bias of Gradient Descent on Reparametrized Models: On
  Equivalence to Mirror Descent
Implicit Bias of Gradient Descent on Reparametrized Models: On Equivalence to Mirror Descent
Zhiyuan Li
Tianhao Wang
Jason D. Lee
Sanjeev Arora
42
27
0
08 Jul 2022
Tensor-on-Tensor Regression: Riemannian Optimization,
  Over-parameterization, Statistical-computational Gap, and Their Interplay
Tensor-on-Tensor Regression: Riemannian Optimization, Over-parameterization, Statistical-computational Gap, and Their Interplay
Yuetian Luo
Anru R. Zhang
29
19
0
17 Jun 2022
Reconstructing Training Data from Trained Neural Networks
Reconstructing Training Data from Trained Neural Networks
Niv Haim
Gal Vardi
Gilad Yehudai
Ohad Shamir
Michal Irani
40
132
0
15 Jun 2022
Understanding the Generalization Benefit of Normalization Layers:
  Sharpness Reduction
Understanding the Generalization Benefit of Normalization Layers: Sharpness Reduction
Kaifeng Lyu
Zhiyuan Li
Sanjeev Arora
FAtt
40
70
0
14 Jun 2022
Gradient flow dynamics of shallow ReLU networks for square loss and
  orthogonal inputs
Gradient flow dynamics of shallow ReLU networks for square loss and orthogonal inputs
Etienne Boursier
Loucas Pillaud-Vivien
Nicolas Flammarion
ODL
24
58
0
02 Jun 2022
Machine Learning and Deep Learning -- A review for Ecologists
Machine Learning and Deep Learning -- A review for Ecologists
Maximilian Pichler
F. Hartig
45
127
0
11 Apr 2022
Robust Training under Label Noise by Over-parameterization
Robust Training under Label Noise by Over-parameterization
Sheng Liu
Zhihui Zhu
Qing Qu
Chong You
NoLa
OOD
27
106
0
28 Feb 2022
Implicit Regularization in Hierarchical Tensor Factorization and Deep
  Convolutional Neural Networks
Implicit Regularization in Hierarchical Tensor Factorization and Deep Convolutional Neural Networks
Noam Razin
Asaf Maman
Nadav Cohen
46
29
0
27 Jan 2022
Variational autoencoders in the presence of low-dimensional data:
  landscape and implicit bias
Variational autoencoders in the presence of low-dimensional data: landscape and implicit bias
Frederic Koehler
Viraj Mehta
Chenghui Zhou
Andrej Risteski
DRL
36
12
0
13 Dec 2021
On Margin Maximization in Linear and ReLU Networks
On Margin Maximization in Linear and ReLU Networks
Gal Vardi
Ohad Shamir
Nathan Srebro
50
28
0
06 Oct 2021
Small random initialization is akin to spectral learning: Optimization
  and generalization guarantees for overparameterized low-rank matrix
  reconstruction
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
On the Implicit Bias of Initialization Shape: Beyond Infinitesimal
  Mirror Descent
On the Implicit Bias of Initialization Shape: Beyond Infinitesimal Mirror Descent
Shahar Azulay
E. Moroshko
Mor Shpigel Nacson
Blake E. Woodworth
Nathan Srebro
Amir Globerson
Daniel Soudry
AI4CE
33
73
0
19 Feb 2021
1