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1706.08947
Cited By
Exploring Generalization in Deep Learning
27 June 2017
Behnam Neyshabur
Srinadh Bhojanapalli
David A. McAllester
Nathan Srebro
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Papers citing
"Exploring Generalization in Deep Learning"
50 / 308 papers shown
Title
Discovering and Explaining the Representation Bottleneck of Graph Neural Networks from Multi-order Interactions
Fang Wu
Siyuan Li
Lirong Wu
Dragomir R. Radev
Stan Z. Li
27
2
0
15 May 2022
Synthetic Data -- what, why and how?
James Jordon
Lukasz Szpruch
F. Houssiau
M. Bottarelli
Giovanni Cherubin
Carsten Maple
Samuel N. Cohen
Adrian Weller
40
109
0
06 May 2022
Enhancing Adversarial Training with Second-Order Statistics of Weights
Gao Jin
Xinping Yi
Wei Huang
S. Schewe
Xiaowei Huang
AAML
26
47
0
11 Mar 2022
QDrop: Randomly Dropping Quantization for Extremely Low-bit Post-Training Quantization
Xiuying Wei
Ruihao Gong
Yuhang Li
Xianglong Liu
F. Yu
MQ
VLM
19
166
0
11 Mar 2022
PACTran: PAC-Bayesian Metrics for Estimating the Transferability of Pretrained Models to Classification Tasks
Nan Ding
Xi Chen
Tomer Levinboim
Soravit Changpinyo
Radu Soricut
22
26
0
10 Mar 2022
β
β
β
-DARTS: Beta-Decay Regularization for Differentiable Architecture Search
Peng Ye
Baopu Li
Yikang Li
Tao Chen
Jiayuan Fan
Wanli Ouyang
16
101
0
03 Mar 2022
Stability vs Implicit Bias of Gradient Methods on Separable Data and Beyond
Matan Schliserman
Tomer Koren
24
23
0
27 Feb 2022
Adversarial robustness of sparse local Lipschitz predictors
Ramchandran Muthukumar
Jeremias Sulam
AAML
32
13
0
26 Feb 2022
Accountability in an Algorithmic Society: Relationality, Responsibility, and Robustness in Machine Learning
A. Feder Cooper
Emanuel Moss
Benjamin Laufer
Helen Nissenbaum
MLAU
24
85
0
10 Feb 2022
The no-free-lunch theorems of supervised learning
T. Sterkenburg
Peter Grünwald
FedML
24
56
0
09 Feb 2022
Penalizing Gradient Norm for Efficiently Improving Generalization in Deep Learning
Yang Zhao
Hao Zhang
Xiuyuan Hu
30
116
0
08 Feb 2022
Evaluating natural language processing models with generalization metrics that do not need access to any training or testing data
Yaoqing Yang
Ryan Theisen
Liam Hodgkinson
Joseph E. Gonzalez
Kannan Ramchandran
Charles H. Martin
Michael W. Mahoney
86
17
0
06 Feb 2022
Anticorrelated Noise Injection for Improved Generalization
Antonio Orvieto
Hans Kersting
F. Proske
Francis R. Bach
Aurelien Lucchi
53
44
0
06 Feb 2022
Demystify Optimization and Generalization of Over-parameterized PAC-Bayesian Learning
Wei Huang
Chunrui Liu
Yilan Chen
Tianyu Liu
R. Xu
BDL
MLT
19
2
0
04 Feb 2022
Non-Vacuous Generalisation Bounds for Shallow Neural Networks
Felix Biggs
Benjamin Guedj
BDL
30
26
0
03 Feb 2022
On the Power-Law Hessian Spectrums in Deep Learning
Zeke Xie
Qian-Yuan Tang
Yunfeng Cai
Mingming Sun
P. Li
ODL
42
9
0
31 Jan 2022
Low-Pass Filtering SGD for Recovering Flat Optima in the Deep Learning Optimization Landscape
Devansh Bisla
Jing Wang
A. Choromańska
25
34
0
20 Jan 2022
Neighborhood Region Smoothing Regularization for Finding Flat Minima In Deep Neural Networks
Yang Zhao
Hao Zhang
22
1
0
16 Jan 2022
Perspective Transformation Layer
Nishant Khatri
Agnibh Dasgupta
Yucong Shen
Xinru Zhong
F. Shih
25
3
0
14 Jan 2022
Class-Incremental Continual Learning into the eXtended DER-verse
Matteo Boschini
Lorenzo Bonicelli
Pietro Buzzega
Angelo Porrello
Simone Calderara
CLL
BDL
26
128
0
03 Jan 2022
Depth and Feature Learning are Provably Beneficial for Neural Network Discriminators
Carles Domingo-Enrich
MLT
MDE
15
0
0
27 Dec 2021
Visualizing the Loss Landscape of Winning Lottery Tickets
Robert Bain
UQCV
25
3
0
16 Dec 2021
On the Impact of Hard Adversarial Instances on Overfitting in Adversarial Training
Chen Liu
Zhichao Huang
Mathieu Salzmann
Tong Zhang
Sabine Süsstrunk
AAML
20
13
0
14 Dec 2021
Generalization Error Bounds for Iterative Recovery Algorithms Unfolded as Neural Networks
Ekkehard Schnoor
Arash Behboodi
Holger Rauhut
16
13
0
08 Dec 2021
Learning Theory Can (Sometimes) Explain Generalisation in Graph Neural Networks
P. Esser
L. C. Vankadara
D. Ghoshdastidar
28
53
0
07 Dec 2021
Multi-scale Feature Learning Dynamics: Insights for Double Descent
Mohammad Pezeshki
Amartya Mitra
Yoshua Bengio
Guillaume Lajoie
61
25
0
06 Dec 2021
On the Convergence of Shallow Neural Network Training with Randomly Masked Neurons
Fangshuo Liao
Anastasios Kyrillidis
38
16
0
05 Dec 2021
Intrinsic Dimension, Persistent Homology and Generalization in Neural Networks
Tolga Birdal
Aaron Lou
Leonidas J. Guibas
Umut cSimcsekli
30
61
0
25 Nov 2021
Subspace Adversarial Training
Tao Li
Yingwen Wu
Sizhe Chen
Kun Fang
Xiaolin Huang
AAML
OOD
41
56
0
24 Nov 2021
Variational encoder geostatistical analysis (VEGAS) with an application to large scale riverine bathymetry
M. Forghani
Yizhou Qian
Jonghyun Lee
Matthew W. Farthing
T. Hesser
P. Kitanidis
Eric F. Darve
11
8
0
23 Nov 2021
Discovering and Explaining the Representation Bottleneck of DNNs
Huiqi Deng
Qihan Ren
Hao Zhang
Quanshi Zhang
39
59
0
11 Nov 2021
GBK-GNN: Gated Bi-Kernel Graph Neural Networks for Modeling Both Homophily and Heterophily
Lun Du
Xiaozhou Shi
Qiang Fu
Xiaojun Ma
Hengyu Liu
Shi Han
Dongmei Zhang
40
104
0
29 Oct 2021
RoMA: Robust Model Adaptation for Offline Model-based Optimization
Sihyun Yu
Sungsoo Ahn
Le Song
Jinwoo Shin
OffRL
27
31
0
27 Oct 2021
Does the Data Induce Capacity Control in Deep Learning?
Rubing Yang
J. Mao
Pratik Chaudhari
27
15
0
27 Oct 2021
In Search of Probeable Generalization Measures
Jonathan Jaegerman
Khalil Damouni
M. M. Ankaralı
Konstantinos N. Plataniotis
19
2
0
23 Oct 2021
Behavioral Experiments for Understanding Catastrophic Forgetting
Samuel J. Bell
Neil D. Lawrence
27
4
0
20 Oct 2021
Interpretive Blindness
Nicholas M. Asher
Julie Hunter
14
0
0
19 Oct 2021
The Role of Permutation Invariance in Linear Mode Connectivity of Neural Networks
R. Entezari
Hanie Sedghi
O. Saukh
Behnam Neyshabur
MoMe
37
216
0
12 Oct 2021
New Insights into Graph Convolutional Networks using Neural Tangent Kernels
Mahalakshmi Sabanayagam
P. Esser
D. Ghoshdastidar
21
6
0
08 Oct 2021
Label Noise in Adversarial Training: A Novel Perspective to Study Robust Overfitting
Chengyu Dong
Liyuan Liu
Jingbo Shang
NoLa
AAML
56
18
0
07 Oct 2021
On the Generalization of Models Trained with SGD: Information-Theoretic Bounds and Implications
Ziqiao Wang
Yongyi Mao
FedML
MLT
37
22
0
07 Oct 2021
On Margin Maximization in Linear and ReLU Networks
Gal Vardi
Ohad Shamir
Nathan Srebro
50
28
0
06 Oct 2021
VC dimension of partially quantized neural networks in the overparametrized regime
Yutong Wang
Clayton D. Scott
20
1
0
06 Oct 2021
Spectral Bias in Practice: The Role of Function Frequency in Generalization
Sara Fridovich-Keil
Raphael Gontijo-Lopes
Rebecca Roelofs
41
28
0
06 Oct 2021
On the Impact of Stable Ranks in Deep Nets
B. Georgiev
L. Franken
Mayukh Mukherjee
Georgios Arvanitidis
13
3
0
05 Oct 2021
Exploring the Limits of Large Scale Pre-training
Samira Abnar
Mostafa Dehghani
Behnam Neyshabur
Hanie Sedghi
AI4CE
60
114
0
05 Oct 2021
Perturbated Gradients Updating within Unit Space for Deep Learning
Ching-Hsun Tseng
Liu Cheng
Shin-Jye Lee
Xiaojun Zeng
40
5
0
01 Oct 2021
Adversarial Parameter Defense by Multi-Step Risk Minimization
Zhiyuan Zhang
Ruixuan Luo
Xuancheng Ren
Qi Su
Liangyou Li
Xu Sun
AAML
23
6
0
07 Sep 2021
Benchmarking the Robustness of Instance Segmentation Models
Said Fahri Altindis
Yusuf Dalva
Hamza Pehlivan
Aysegül Dündar
VLM
OOD
29
12
0
02 Sep 2021
NeuroCartography: Scalable Automatic Visual Summarization of Concepts in Deep Neural Networks
Haekyu Park
Nilaksh Das
Rahul Duggal
Austin P. Wright
Omar Shaikh
Fred Hohman
Duen Horng Chau
HAI
19
25
0
29 Aug 2021
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