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A Mean-field Analysis of Deep ResNet and Beyond: Towards Provable
  Optimization Via Overparameterization From Depth

A Mean-field Analysis of Deep ResNet and Beyond: Towards Provable Optimization Via Overparameterization From Depth

11 March 2020
Yiping Lu
Chao Ma
Yulong Lu
Jianfeng Lu
Lexing Ying
    MLT
ArXivPDFHTML

Papers citing "A Mean-field Analysis of Deep ResNet and Beyond: Towards Provable Optimization Via Overparameterization From Depth"

22 / 22 papers shown
Title
Convergence of Time-Averaged Mean Field Gradient Descent Dynamics for Continuous Multi-Player Zero-Sum Games
Convergence of Time-Averaged Mean Field Gradient Descent Dynamics for Continuous Multi-Player Zero-Sum Games
Yulong Lu
Pierre Monmarché
MLT
34
0
0
12 May 2025
Understanding the training of infinitely deep and wide ResNets with
  Conditional Optimal Transport
Understanding the training of infinitely deep and wide ResNets with Conditional Optimal Transport
Raphael Barboni
Gabriel Peyré
Franccois-Xavier Vialard
37
3
0
19 Mar 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
30
11
0
03 Oct 2023
Global Optimality of Elman-type RNN in the Mean-Field Regime
Global Optimality of Elman-type RNN in the Mean-Field Regime
Andrea Agazzi
Jian-Xiong Lu
Sayan Mukherjee
MLT
26
1
0
12 Mar 2023
Over-Parameterization Exponentially Slows Down Gradient Descent for
  Learning a Single Neuron
Over-Parameterization Exponentially Slows Down Gradient Descent for Learning a Single Neuron
Weihang Xu
S. Du
29
16
0
20 Feb 2023
ZiCo: Zero-shot NAS via Inverse Coefficient of Variation on Gradients
ZiCo: Zero-shot NAS via Inverse Coefficient of Variation on Gradients
Guihong Li
Yuedong Yang
Kartikeya Bhardwaj
R. Marculescu
36
60
0
26 Jan 2023
Asymptotic Analysis of Deep Residual Networks
Asymptotic Analysis of Deep Residual Networks
R. Cont
Alain Rossier
Renyuan Xu
24
4
0
15 Dec 2022
Deep Generalized Schrödinger Bridge
Deep Generalized Schrödinger Bridge
Guan-Horng Liu
T. Chen
Oswin So
Evangelos A. Theodorou
OT
AI4CE
8
34
0
20 Sep 2022
Do Residual Neural Networks discretize Neural Ordinary Differential
  Equations?
Do Residual Neural Networks discretize Neural Ordinary Differential Equations?
Michael E. Sander
Pierre Ablin
Gabriel Peyré
32
25
0
29 May 2022
Provably convergent quasistatic dynamics for mean-field two-player
  zero-sum games
Provably convergent quasistatic dynamics for mean-field two-player zero-sum games
Chao Ma
Lexing Ying
MLT
27
11
0
15 Feb 2022
On the Convergence of Shallow Neural Network Training with Randomly
  Masked Neurons
On the Convergence of Shallow Neural Network Training with Randomly Masked Neurons
Fangshuo Liao
Anastasios Kyrillidis
36
16
0
05 Dec 2021
Subquadratic Overparameterization for Shallow Neural Networks
Subquadratic Overparameterization for Shallow Neural Networks
Chaehwan Song
Ali Ramezani-Kebrya
Thomas Pethick
Armin Eftekhari
V. Cevher
24
32
0
02 Nov 2021
Why Lottery Ticket Wins? A Theoretical Perspective of Sample Complexity
  on Pruned Neural Networks
Why Lottery Ticket Wins? A Theoretical Perspective of Sample Complexity on Pruned Neural Networks
Shuai Zhang
Meng Wang
Sijia Liu
Pin-Yu Chen
Jinjun Xiong
UQCV
MLT
21
13
0
12 Oct 2021
On the Global Convergence of Gradient Descent for multi-layer ResNets in
  the mean-field regime
On the Global Convergence of Gradient Descent for multi-layer ResNets in the mean-field regime
Zhiyan Ding
Shi Chen
Qin Li
S. Wright
MLT
AI4CE
30
11
0
06 Oct 2021
ResIST: Layer-Wise Decomposition of ResNets for Distributed Training
ResIST: Layer-Wise Decomposition of ResNets for Distributed Training
Chen Dun
Cameron R. Wolfe
C. Jermaine
Anastasios Kyrillidis
16
21
0
02 Jul 2021
Scaling Properties of Deep Residual Networks
Scaling Properties of Deep Residual Networks
A. Cohen
R. Cont
Alain Rossier
Renyuan Xu
17
18
0
25 May 2021
Global Convergence of Three-layer Neural Networks in the Mean Field
  Regime
Global Convergence of Three-layer Neural Networks in the Mean Field Regime
H. Pham
Phan-Minh Nguyen
MLT
AI4CE
41
19
0
11 May 2021
A Local Convergence Theory for Mildly Over-Parameterized Two-Layer
  Neural Network
A Local Convergence Theory for Mildly Over-Parameterized Two-Layer Neural Network
Mo Zhou
Rong Ge
Chi Jin
74
44
0
04 Feb 2021
Neural Network Approximation: Three Hidden Layers Are Enough
Neural Network Approximation: Three Hidden Layers Are Enough
Zuowei Shen
Haizhao Yang
Shijun Zhang
19
115
0
25 Oct 2020
A Differential Game Theoretic Neural Optimizer for Training Residual
  Networks
A Differential Game Theoretic Neural Optimizer for Training Residual Networks
Guan-Horng Liu
T. Chen
Evangelos A. Theodorou
21
2
0
17 Jul 2020
Two-Layer Neural Networks for Partial Differential Equations:
  Optimization and Generalization Theory
Two-Layer Neural Networks for Partial Differential Equations: Optimization and Generalization Theory
Tao Luo
Haizhao Yang
29
73
0
28 Jun 2020
Representing smooth functions as compositions of near-identity functions
  with implications for deep network optimization
Representing smooth functions as compositions of near-identity functions with implications for deep network optimization
Peter L. Bartlett
S. Evans
Philip M. Long
71
31
0
13 Apr 2018
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