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The intriguing role of module criticality in the generalization of deep
  networks

The intriguing role of module criticality in the generalization of deep networks

2 December 2019
Niladri S. Chatterji
Behnam Neyshabur
Hanie Sedghi
ArXivPDFHTML

Papers citing "The intriguing role of module criticality in the generalization of deep networks"

25 / 25 papers shown
Title
A Margin-based Multiclass Generalization Bound via Geometric Complexity
A Margin-based Multiclass Generalization Bound via Geometric Complexity
Michael Munn
Benoit Dherin
Javier Gonzalvo
UQCV
42
2
0
28 May 2024
Securely Fine-tuning Pre-trained Encoders Against Adversarial Examples
Securely Fine-tuning Pre-trained Encoders Against Adversarial Examples
Ziqi Zhou
Minghui Li
Wei Liu
Shengshan Hu
Yechao Zhang
Wei Wan
Lulu Xue
Leo Yu Zhang
Dezhong Yao
Hai Jin
SILM
AAML
52
9
0
16 Mar 2024
Gradient-based Parameter Selection for Efficient Fine-Tuning
Gradient-based Parameter Selection for Efficient Fine-Tuning
Zhi Zhang
Qizhe Zhang
Zijun Gao
Renrui Zhang
Ekaterina Shutova
Shiji Zhou
Shanghang Zhang
33
15
0
15 Dec 2023
Layer-wise Linear Mode Connectivity
Layer-wise Linear Mode Connectivity
Linara Adilova
Maksym Andriushchenko
Michael Kamp
Asja Fischer
Martin Jaggi
FedML
FAtt
MoMe
40
15
0
13 Jul 2023
Sensitivity-Aware Visual Parameter-Efficient Fine-Tuning
Sensitivity-Aware Visual Parameter-Efficient Fine-Tuning
Haoyu He
Jianfei Cai
Jing Zhang
Dacheng Tao
Bohan Zhuang
VPVLM
22
50
0
15 Mar 2023
On the Lipschitz Constant of Deep Networks and Double Descent
On the Lipschitz Constant of Deep Networks and Double Descent
Matteo Gamba
Hossein Azizpour
Mårten Björkman
33
7
0
28 Jan 2023
Limitations of Information-Theoretic Generalization Bounds for Gradient
  Descent Methods in Stochastic Convex Optimization
Limitations of Information-Theoretic Generalization Bounds for Gradient Descent Methods in Stochastic Convex Optimization
Mahdi Haghifam
Borja Rodríguez Gálvez
Ragnar Thobaben
Mikael Skoglund
Daniel M. Roy
Gintare Karolina Dziugaite
31
17
0
27 Dec 2022
Leveraging Unlabeled Data to Track Memorization
Leveraging Unlabeled Data to Track Memorization
Mahsa Forouzesh
Hanie Sedghi
Patrick Thiran
NoLa
TDI
39
4
0
08 Dec 2022
Surgical Fine-Tuning Improves Adaptation to Distribution Shifts
Surgical Fine-Tuning Improves Adaptation to Distribution Shifts
Yoonho Lee
Annie S. Chen
Fahim Tajwar
Ananya Kumar
Huaxiu Yao
Percy Liang
Chelsea Finn
OOD
66
199
0
20 Oct 2022
Byzantines can also Learn from History: Fall of Centered Clipping in
  Federated Learning
Byzantines can also Learn from History: Fall of Centered Clipping in Federated Learning
Kerem Ozfatura
Emre Ozfatura
Alptekin Kupcu
Deniz Gunduz
AAML
FedML
41
13
0
21 Aug 2022
Generalized Federated Learning via Sharpness Aware Minimization
Generalized Federated Learning via Sharpness Aware Minimization
Zhe Qu
Xingyu Li
Rui Duan
Yaojiang Liu
Bo Tang
Zhuo Lu
FedML
45
131
0
06 Jun 2022
Linear Connectivity Reveals Generalization Strategies
Linear Connectivity Reveals Generalization Strategies
Jeevesh Juneja
Rachit Bansal
Kyunghyun Cho
João Sedoc
Naomi Saphra
244
45
0
24 May 2022
Weight Expansion: A New Perspective on Dropout and Generalization
Weight Expansion: A New Perspective on Dropout and Generalization
Gao Jin
Xinping Yi
Pengfei Yang
Lijun Zhang
S. Schewe
Xiaowei Huang
29
5
0
23 Jan 2022
DR3: Value-Based Deep Reinforcement Learning Requires Explicit
  Regularization
DR3: Value-Based Deep Reinforcement Learning Requires Explicit Regularization
Aviral Kumar
Rishabh Agarwal
Tengyu Ma
Aaron Courville
George Tucker
Sergey Levine
OffRL
31
65
0
09 Dec 2021
Visualizing the Emergence of Intermediate Visual Patterns in DNNs
Visualizing the Emergence of Intermediate Visual Patterns in DNNs
Mingjie Li
Shaobo Wang
Quanshi Zhang
46
11
0
05 Nov 2021
Exploring Heterogeneous Characteristics of Layers in ASR Models for More
  Efficient Training
Exploring Heterogeneous Characteristics of Layers in ASR Models for More Efficient Training
Lillian Zhou
Dhruv Guliani
Andreas Kabel
Giovanni Motta
F. Beaufays
26
1
0
08 Oct 2021
Perturbated Gradients Updating within Unit Space for Deep Learning
Perturbated Gradients Updating within Unit Space for Deep Learning
Ching-Hsun Tseng
Liu Cheng
Shin-Jye Lee
Xiaojun Zeng
50
5
0
01 Oct 2021
What can linear interpolation of neural network loss landscapes tell us?
What can linear interpolation of neural network loss landscapes tell us?
Tiffany J. Vlaar
Jonathan Frankle
MoMe
30
27
0
30 Jun 2021
ASAM: Adaptive Sharpness-Aware Minimization for Scale-Invariant Learning
  of Deep Neural Networks
ASAM: Adaptive Sharpness-Aware Minimization for Scale-Invariant Learning of Deep Neural Networks
Jungmin Kwon
Jeongseop Kim
Hyunseong Park
I. Choi
48
282
0
23 Feb 2021
NeurIPS 2020 Competition: Predicting Generalization in Deep Learning
NeurIPS 2020 Competition: Predicting Generalization in Deep Learning
Yiding Jiang
Pierre Foret
Scott Yak
Daniel M. Roy
H. Mobahi
Gintare Karolina Dziugaite
Samy Bengio
Suriya Gunasekar
Isabelle M Guyon
Behnam Neyshabur Google Research
OOD
24
55
0
14 Dec 2020
Rethinking the Value of Transformer Components
Rethinking the Value of Transformer Components
Wenxuan Wang
Zhaopeng Tu
24
38
0
07 Nov 2020
Sharpness-Aware Minimization for Efficiently Improving Generalization
Sharpness-Aware Minimization for Efficiently Improving Generalization
Pierre Foret
Ariel Kleiner
H. Mobahi
Behnam Neyshabur
AAML
127
1,286
0
03 Oct 2020
Analysis of Generalizability of Deep Neural Networks Based on the
  Complexity of Decision Boundary
Analysis of Generalizability of Deep Neural Networks Based on the Complexity of Decision Boundary
Shuyue Guan
Murray H. Loew
30
25
0
16 Sep 2020
PAC-Bayesian Margin Bounds for Convolutional Neural Networks
PAC-Bayesian Margin Bounds for Convolutional Neural Networks
Konstantinos Pitas
Mike Davies
P. Vandergheynst
BDL
54
12
0
30 Dec 2017
Norm-Based Capacity Control in Neural Networks
Norm-Based Capacity Control in Neural Networks
Behnam Neyshabur
Ryota Tomioka
Nathan Srebro
127
577
0
27 Feb 2015
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