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Gradient descent aligns the layers of deep linear networks

Gradient descent aligns the layers of deep linear networks

4 October 2018
Ziwei Ji
Matus Telgarsky
ArXivPDFHTML

Papers citing "Gradient descent aligns the layers of deep linear networks"

50 / 61 papers shown
Title
Embedding principle of homogeneous neural network for classification problem
Embedding principle of homogeneous neural network for classification problem
Jiahan Zhang
Tao Luo
Yaoyu Zhang
2
0
0
18 May 2025
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
59
0
0
11 Apr 2025
The late-stage training dynamics of (stochastic) subgradient descent on homogeneous neural networks
Sholom Schechtman
Nicolas Schreuder
173
0
0
08 Feb 2025
Grokking at the Edge of Numerical Stability
Grokking at the Edge of Numerical Stability
Lucas Prieto
Melih Barsbey
Pedro A.M. Mediano
Tolga Birdal
48
3
0
08 Jan 2025
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
12
0
06 Jun 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
Implicit Bias of AdamW: $\ell_\infty$ Norm Constrained Optimization
Implicit Bias of AdamW: ℓ∞\ell_\inftyℓ∞​ Norm Constrained Optimization
Shuo Xie
Zhiyuan Li
OffRL
47
13
0
05 Apr 2024
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
ReLU Neural Networks with Linear Layers are Biased Towards Single- and Multi-Index Models
ReLU Neural Networks with Linear Layers are Biased Towards Single- and Multi-Index Models
Suzanna Parkinson
Greg Ongie
Rebecca Willett
65
6
0
24 May 2023
Implicit Bias of Gradient Descent for Logistic Regression at the Edge of
  Stability
Implicit Bias of Gradient Descent for Logistic Regression at the Edge of Stability
Jingfeng Wu
Vladimir Braverman
Jason D. Lee
32
17
0
19 May 2023
Phase Diagram of Initial Condensation for Two-layer Neural Networks
Phase Diagram of Initial Condensation for Two-layer Neural Networks
Zheng Chen
Yuqing Li
Tao Luo
Zhaoguang Zhou
Z. Xu
MLT
AI4CE
49
8
0
12 Mar 2023
Provable Pathways: Learning Multiple Tasks over Multiple Paths
Provable Pathways: Learning Multiple Tasks over Multiple Paths
Yingcong Li
Samet Oymak
MoE
26
4
0
08 Mar 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
Regression as Classification: Influence of Task Formulation on Neural
  Network Features
Regression as Classification: Influence of Task Formulation on Neural Network Features
Lawrence Stewart
Francis R. Bach
Quentin Berthet
Jean-Philippe Vert
29
24
0
10 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
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
Magnitude and Angle Dynamics in Training Single ReLU Neurons
Magnitude and Angle Dynamics in Training Single ReLU Neurons
Sangmin Lee
Byeongsu Sim
Jong Chul Ye
MLT
96
6
0
27 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
The Neural Race Reduction: Dynamics of Abstraction in Gated Networks
The Neural Race Reduction: Dynamics of Abstraction in Gated Networks
Andrew M. Saxe
Shagun Sodhani
Sam Lewallen
AI4CE
30
34
0
21 Jul 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
Neural Collapse: A Review on Modelling Principles and Generalization
Neural Collapse: A Review on Modelling Principles and Generalization
Vignesh Kothapalli
25
71
0
08 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
Convergence of gradient descent for deep neural networks
Convergence of gradient descent for deep neural networks
S. Chatterjee
ODL
21
20
0
30 Mar 2022
Explicitising The Implicit Intrepretability of Deep Neural Networks Via
  Duality
Explicitising The Implicit Intrepretability of Deep Neural Networks Via Duality
Chandrashekar Lakshminarayanan
Ashutosh Kumar Singh
A. Rajkumar
AI4CE
26
1
0
01 Mar 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
Benign Overfitting in Adversarially Robust Linear Classification
Benign Overfitting in Adversarially Robust Linear Classification
Jinghui Chen
Yuan Cao
Quanquan Gu
AAML
SILM
34
10
0
31 Dec 2021
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
Understanding Dimensional Collapse in Contrastive Self-supervised
  Learning
Understanding Dimensional Collapse in Contrastive Self-supervised Learning
Li Jing
Pascal Vincent
Yann LeCun
Yuandong Tian
SSL
25
338
0
18 Oct 2021
Parallel Deep Neural Networks Have Zero Duality Gap
Parallel Deep Neural Networks Have Zero Duality Gap
Yifei Wang
Tolga Ergen
Mert Pilanci
79
10
0
13 Oct 2021
Self-supervised Learning is More Robust to Dataset Imbalance
Self-supervised Learning is More Robust to Dataset Imbalance
Hong Liu
Jeff Z. HaoChen
Adrien Gaidon
Tengyu Ma
OOD
SSL
33
157
0
11 Oct 2021
Large Learning Rate Tames Homogeneity: Convergence and Balancing Effect
Large Learning Rate Tames Homogeneity: Convergence and Balancing Effect
Yuqing Wang
Minshuo Chen
T. Zhao
Molei Tao
AI4CE
57
40
0
07 Oct 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
Interpolation can hurt robust generalization even when there is no noise
Interpolation can hurt robust generalization even when there is no noise
Konstantin Donhauser
Alexandru cTifrea
Michael Aerni
Reinhard Heckel
Fanny Yang
34
14
0
05 Aug 2021
A Theoretical Analysis of Fine-tuning with Linear Teachers
A Theoretical Analysis of Fine-tuning with Linear Teachers
Gal Shachaf
Alon Brutzkus
Amir Globerson
34
17
0
04 Jul 2021
Understanding the role of importance weighting for deep learning
Understanding the role of importance weighting for deep learning
Da Xu
Yuting Ye
Chuanwei Ruan
FAtt
39
43
0
28 Mar 2021
Noisy Gradient Descent Converges to Flat Minima for Nonconvex Matrix
  Factorization
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
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
The Implicit Bias for Adaptive Optimization Algorithms on Homogeneous
  Neural Networks
The Implicit Bias for Adaptive Optimization Algorithms on Homogeneous Neural Networks
Bohan Wang
Qi Meng
Wei Chen
Tie-Yan Liu
30
33
0
11 Dec 2020
Align, then memorise: the dynamics of learning with feedback alignment
Align, then memorise: the dynamics of learning with feedback alignment
Maria Refinetti
Stéphane dÁscoli
Ruben Ohana
Sebastian Goldt
26
36
0
24 Nov 2020
Implicit Bias in Deep Linear Classification: Initialization Scale vs
  Training Accuracy
Implicit Bias in Deep Linear Classification: Initialization Scale vs Training Accuracy
E. Moroshko
Suriya Gunasekar
Blake E. Woodworth
J. Lee
Nathan Srebro
Daniel Soudry
35
85
0
13 Jul 2020
When Does Preconditioning Help or Hurt Generalization?
When Does Preconditioning Help or Hurt Generalization?
S. Amari
Jimmy Ba
Roger C. Grosse
Xuechen Li
Atsushi Nitanda
Taiji Suzuki
Denny Wu
Ji Xu
36
32
0
18 Jun 2020
Shape Matters: Understanding the Implicit Bias of the Noise Covariance
Shape Matters: Understanding the Implicit Bias of the Noise Covariance
Jeff Z. HaoChen
Colin Wei
J. Lee
Tengyu Ma
29
93
0
15 Jun 2020
To Each Optimizer a Norm, To Each Norm its Generalization
To Each Optimizer a Norm, To Each Norm its Generalization
Sharan Vaswani
Reza Babanezhad
Jose Gallego
Aaron Mishkin
Simon Lacoste-Julien
Nicolas Le Roux
26
8
0
11 Jun 2020
Directional convergence and alignment in deep learning
Directional convergence and alignment in deep learning
Ziwei Ji
Matus Telgarsky
17
162
0
11 Jun 2020
Implicit Regularization in Deep Learning May Not Be Explainable by Norms
Implicit Regularization in Deep Learning May Not Be Explainable by Norms
Noam Razin
Nadav Cohen
24
155
0
13 May 2020
An Optimization and Generalization Analysis for Max-Pooling Networks
An Optimization and Generalization Analysis for Max-Pooling Networks
Alon Brutzkus
Amir Globerson
MLT
AI4CE
16
4
0
22 Feb 2020
Implicit Bias of Gradient Descent for Wide Two-layer Neural Networks
  Trained with the Logistic Loss
Implicit Bias of Gradient Descent for Wide Two-layer Neural Networks Trained with the Logistic Loss
Lénaïc Chizat
Francis R. Bach
MLT
39
327
0
11 Feb 2020
Optimization for deep learning: theory and algorithms
Optimization for deep learning: theory and algorithms
Ruoyu Sun
ODL
19
168
0
19 Dec 2019
Global Convergence of Gradient Descent for Deep Linear Residual Networks
Global Convergence of Gradient Descent for Deep Linear Residual Networks
Lei Wu
Qingcan Wang
Chao Ma
ODL
AI4CE
28
22
0
02 Nov 2019
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