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The Local Elasticity of Neural Networks

The Local Elasticity of Neural Networks

15 October 2019
Hangfeng He
Weijie J. Su
ArXivPDFHTML

Papers citing "The Local Elasticity of Neural Networks"

15 / 15 papers shown
Title
Elephant Neural Networks: Born to Be a Continual Learner
Elephant Neural Networks: Born to Be a Continual Learner
Qingfeng Lan
A. R. Mahmood
CLL
42
9
0
02 Oct 2023
A Law of Data Separation in Deep Learning
A Law of Data Separation in Deep Learning
Hangfeng He
Weijie J. Su
OOD
24
36
0
31 Oct 2022
Global Convergence of SGD On Two Layer Neural Nets
Global Convergence of SGD On Two Layer Neural Nets
Pulkit Gopalani
Anirbit Mukherjee
23
5
0
20 Oct 2022
TiDAL: Learning Training Dynamics for Active Learning
TiDAL: Learning Training Dynamics for Active Learning
Seong Min Kye
Kwanghee Choi
Hyeongmin Byun
Buru Chang
34
13
0
13 Oct 2022
Neural Collapse: A Review on Modelling Principles and Generalization
Neural Collapse: A Review on Modelling Principles and Generalization
Vignesh Kothapalli
21
71
0
08 Jun 2022
On the Interpretability of Regularisation for Neural Networks Through
  Model Gradient Similarity
On the Interpretability of Regularisation for Neural Networks Through Model Gradient Similarity
Vincent Szolnoky
Viktor Andersson
Balázs Kulcsár
Rebecka Jörnsten
37
5
0
25 May 2022
Imitating Deep Learning Dynamics via Locally Elastic Stochastic
  Differential Equations
Imitating Deep Learning Dynamics via Locally Elastic Stochastic Differential Equations
Jiayao Zhang
Hua Wang
Weijie J. Su
32
7
0
11 Oct 2021
Fishr: Invariant Gradient Variances for Out-of-Distribution
  Generalization
Fishr: Invariant Gradient Variances for Out-of-Distribution Generalization
Alexandre Ramé
Corentin Dancette
Matthieu Cord
OOD
38
204
0
07 Sep 2021
Semi-Supervised Active Learning with Temporal Output Discrepancy
Semi-Supervised Active Learning with Temporal Output Discrepancy
Siyu Huang
Tianyang Wang
Haoyi Xiong
Jun Huan
Dejing Dou
UQCV
25
66
0
29 Jul 2021
Exploring Deep Neural Networks via Layer-Peeled Model: Minority Collapse
  in Imbalanced Training
Exploring Deep Neural Networks via Layer-Peeled Model: Minority Collapse in Imbalanced Training
Cong Fang
Hangfeng He
Qi Long
Weijie J. Su
FAtt
127
165
0
29 Jan 2021
A Random Matrix Theory Approach to Damping in Deep Learning
A Random Matrix Theory Approach to Damping in Deep Learning
Diego Granziol
Nicholas P. Baskerville
AI4CE
ODL
26
2
0
15 Nov 2020
The Break-Even Point on Optimization Trajectories of Deep Neural
  Networks
The Break-Even Point on Optimization Trajectories of Deep Neural Networks
Stanislaw Jastrzebski
Maciej Szymczak
Stanislav Fort
Devansh Arpit
Jacek Tabor
Kyunghyun Cho
Krzysztof J. Geras
47
154
0
21 Feb 2020
Approximation by Combinations of ReLU and Squared ReLU Ridge Functions
  with $ \ell^1 $ and $ \ell^0 $ Controls
Approximation by Combinations of ReLU and Squared ReLU Ridge Functions with ℓ1 \ell^1 ℓ1 and ℓ0 \ell^0 ℓ0 Controls
Jason M. Klusowski
Andrew R. Barron
130
142
0
26 Jul 2016
Benefits of depth in neural networks
Benefits of depth in neural networks
Matus Telgarsky
148
602
0
14 Feb 2016
The Loss Surfaces of Multilayer Networks
The Loss Surfaces of Multilayer Networks
A. Choromańska
Mikael Henaff
Michaël Mathieu
Gerard Ben Arous
Yann LeCun
ODL
179
1,185
0
30 Nov 2014
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