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Understanding deep learning requires rethinking generalization

Understanding deep learning requires rethinking generalization

10 November 2016
Chiyuan Zhang
Samy Bengio
Moritz Hardt
Benjamin Recht
Oriol Vinyals
    HAI
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Papers citing "Understanding deep learning requires rethinking generalization"

50 / 972 papers shown
Title
GraphNorm: A Principled Approach to Accelerating Graph Neural Network
  Training
GraphNorm: A Principled Approach to Accelerating Graph Neural Network Training
Tianle Cai
Shengjie Luo
Keyulu Xu
Di He
Tie-Yan Liu
Liwei Wang
GNN
32
159
0
07 Sep 2020
Witches' Brew: Industrial Scale Data Poisoning via Gradient Matching
Witches' Brew: Industrial Scale Data Poisoning via Gradient Matching
Jonas Geiping
Liam H. Fowl
Yifan Jiang
W. Czaja
Gavin Taylor
Michael Moeller
Tom Goldstein
AAML
19
215
0
04 Sep 2020
Learning explanations that are hard to vary
Learning explanations that are hard to vary
Giambattista Parascandolo
Alexander Neitz
Antonio Orvieto
Luigi Gresele
Bernhard Schölkopf
FAtt
27
178
0
01 Sep 2020
Predicting Training Time Without Training
Predicting Training Time Without Training
L. Zancato
Alessandro Achille
Avinash Ravichandran
Rahul Bhotika
Stefano Soatto
26
24
0
28 Aug 2020
Training Sparse Neural Networks using Compressed Sensing
Training Sparse Neural Networks using Compressed Sensing
Jonathan W. Siegel
Jianhong Chen
Pengchuan Zhang
Jinchao Xu
26
5
0
21 Aug 2020
Obtaining Adjustable Regularization for Free via Iterate Averaging
Obtaining Adjustable Regularization for Free via Iterate Averaging
Jingfeng Wu
Vladimir Braverman
Lin F. Yang
30
2
0
15 Aug 2020
Common pitfalls and recommendations for using machine learning to detect
  and prognosticate for COVID-19 using chest radiographs and CT scans
Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans
M. Roberts
D. Driggs
Matthew Thorpe
J. Gilbey
Michael Yeung
...
Kang Zhang
S. Stranks
James H. F. Rudd
Evis Sala
Carola-Bibiane Schönlieb
OOD
21
766
0
14 Aug 2020
What Neural Networks Memorize and Why: Discovering the Long Tail via
  Influence Estimation
What Neural Networks Memorize and Why: Discovering the Long Tail via Influence Estimation
Vitaly Feldman
Chiyuan Zhang
TDI
46
440
0
09 Aug 2020
Data-driven Meta-set Based Fine-Grained Visual Classification
Data-driven Meta-set Based Fine-Grained Visual Classification
Chuanyi Zhang
Yazhou Yao
Xiangbo Shu
Zechao Li
Zhenmin Tang
Qi Wu
NoLa
21
2
0
06 Aug 2020
Salvage Reusable Samples from Noisy Data for Robust Learning
Salvage Reusable Samples from Noisy Data for Robust Learning
Zeren Sun
Xiansheng Hua
Yazhou Yao
Xiu-Shen Wei
Guosheng Hu
Jian Zhang
NoLa
29
41
0
06 Aug 2020
Multiple Descent: Design Your Own Generalization Curve
Multiple Descent: Design Your Own Generalization Curve
Lin Chen
Yifei Min
M. Belkin
Amin Karbasi
DRL
28
61
0
03 Aug 2020
The Interpolation Phase Transition in Neural Networks: Memorization and
  Generalization under Lazy Training
The Interpolation Phase Transition in Neural Networks: Memorization and Generalization under Lazy Training
Andrea Montanari
Yiqiao Zhong
49
95
0
25 Jul 2020
Learning Noise-Aware Encoder-Decoder from Noisy Labels by Alternating
  Back-Propagation for Saliency Detection
Learning Noise-Aware Encoder-Decoder from Noisy Labels by Alternating Back-Propagation for Saliency Detection
Jing Zhang
Jianwen Xie
Nick Barnes
NoLa
52
57
0
23 Jul 2020
Privacy-preserving Artificial Intelligence Techniques in Biomedicine
Privacy-preserving Artificial Intelligence Techniques in Biomedicine
Reihaneh Torkzadehmahani
Reza Nasirigerdeh
David B. Blumenthal
T. Kacprowski
M. List
...
Harald H. H. W. Schmidt
A. Schwalber
Christof Tschohl
Andrea Wohner
Jan Baumbach
21
60
0
22 Jul 2020
Learning from Noisy Labels with Deep Neural Networks: A Survey
Learning from Noisy Labels with Deep Neural Networks: A Survey
Hwanjun Song
Minseok Kim
Dongmin Park
Yooju Shin
Jae-Gil Lee
NoLa
24
963
0
16 Jul 2020
Explicit Regularisation in Gaussian Noise Injections
Explicit Regularisation in Gaussian Noise Injections
A. Camuto
M. Willetts
Umut Simsekli
Stephen J. Roberts
Chris Holmes
25
55
0
14 Jul 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
Graph Structure of Neural Networks
Graph Structure of Neural Networks
Jiaxuan You
J. Leskovec
Kaiming He
Saining Xie
GNN
27
137
0
13 Jul 2020
Term Revealing: Furthering Quantization at Run Time on Quantized DNNs
Term Revealing: Furthering Quantization at Run Time on Quantized DNNs
H. T. Kung
Bradley McDanel
S. Zhang
MQ
21
9
0
13 Jul 2020
Quantitative Propagation of Chaos for SGD in Wide Neural Networks
Quantitative Propagation of Chaos for SGD in Wide Neural Networks
Valentin De Bortoli
Alain Durmus
Xavier Fontaine
Umut Simsekli
32
25
0
13 Jul 2020
Meta Soft Label Generation for Noisy Labels
Meta Soft Label Generation for Noisy Labels
G. Algan
ilkay Ulusoy
NoLa
30
38
0
11 Jul 2020
How benign is benign overfitting?
How benign is benign overfitting?
Amartya Sanyal
P. Dokania
Varun Kanade
Philip Torr
NoLa
AAML
23
57
0
08 Jul 2020
Contextual-Relation Consistent Domain Adaptation for Semantic
  Segmentation
Contextual-Relation Consistent Domain Adaptation for Semantic Segmentation
Jiaxing Huang
Shijian Lu
Dayan Guan
Xiaobing Zhang
31
125
0
05 Jul 2020
Knowledge Distillation Beyond Model Compression
Knowledge Distillation Beyond Model Compression
F. Sarfraz
Elahe Arani
Bahram Zonooz
20
40
0
03 Jul 2020
Provably Efficient Neural Estimation of Structural Equation Model: An
  Adversarial Approach
Provably Efficient Neural Estimation of Structural Equation Model: An Adversarial Approach
Luofeng Liao
You-Lin Chen
Zhuoran Yang
Bo Dai
Zhaoran Wang
Mladen Kolar
30
33
0
02 Jul 2020
A Revision of Neural Tangent Kernel-based Approaches for Neural Networks
Kyungsu Kim
A. Lozano
Eunho Yang
AAML
35
0
0
02 Jul 2020
GShard: Scaling Giant Models with Conditional Computation and Automatic
  Sharding
GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding
Dmitry Lepikhin
HyoukJoong Lee
Yuanzhong Xu
Dehao Chen
Orhan Firat
Yanping Huang
M. Krikun
Noam M. Shazeer
Z. Chen
MoE
43
1,108
0
30 Jun 2020
Training highly effective connectivities within neural networks with
  randomly initialized, fixed weights
Training highly effective connectivities within neural networks with randomly initialized, fixed weights
Cristian Ivan
Razvan V. Florian
27
4
0
30 Jun 2020
Modeling Generalization in Machine Learning: A Methodological and
  Computational Study
Modeling Generalization in Machine Learning: A Methodological and Computational Study
Pietro Barbiero
Giovanni Squillero
Alberto Tonda
12
35
0
28 Jun 2020
Active Online Learning with Hidden Shifting Domains
Active Online Learning with Hidden Shifting Domains
Yining Chen
Haipeng Luo
Tengyu Ma
Chicheng Zhang
31
5
0
25 Jun 2020
Breaking the Curse of Many Agents: Provable Mean Embedding Q-Iteration
  for Mean-Field Reinforcement Learning
Breaking the Curse of Many Agents: Provable Mean Embedding Q-Iteration for Mean-Field Reinforcement Learning
Lingxiao Wang
Zhuoran Yang
Zhaoran Wang
27
26
0
21 Jun 2020
Gradient descent follows the regularization path for general losses
Gradient descent follows the regularization path for general losses
Ziwei Ji
Miroslav Dudík
Robert Schapire
Matus Telgarsky
AI4CE
FaML
11
60
0
19 Jun 2020
Poisson Learning: Graph Based Semi-Supervised Learning At Very Low Label
  Rates
Poisson Learning: Graph Based Semi-Supervised Learning At Very Low Label Rates
Jeff Calder
Brendan Cook
Matthew Thorpe
D. Slepčev
27
82
0
19 Jun 2020
Statistical and Algorithmic Insights for Semi-supervised Learning with
  Self-training
Statistical and Algorithmic Insights for Semi-supervised Learning with Self-training
Samet Oymak
Talha Cihad Gulcu
19
19
0
19 Jun 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
What Do Neural Networks Learn When Trained With Random Labels?
What Do Neural Networks Learn When Trained With Random Labels?
Hartmut Maennel
Ibrahim M. Alabdulmohsin
Ilya O. Tolstikhin
R. Baldock
Olivier Bousquet
Sylvain Gelly
Daniel Keysers
FedML
48
87
0
18 Jun 2020
Are you wearing a mask? Improving mask detection from speech using
  augmentation by cycle-consistent GANs
Are you wearing a mask? Improving mask detection from speech using augmentation by cycle-consistent GANs
Nicolae-Cuatualin Ristea
Radu Tudor Ionescu
CVBM
6
41
0
17 Jun 2020
Interpolation and Learning with Scale Dependent Kernels
Nicolò Pagliana
Alessandro Rudi
Ernesto De Vito
Lorenzo Rosasco
44
8
0
17 Jun 2020
Neural Anisotropy Directions
Neural Anisotropy Directions
Guillermo Ortiz-Jiménez
Apostolos Modas
Seyed-Mohsen Moosavi-Dezfooli
P. Frossard
34
16
0
17 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
32
94
0
15 Jun 2020
On the training dynamics of deep networks with $L_2$ regularization
On the training dynamics of deep networks with L2L_2L2​ regularization
Aitor Lewkowycz
Guy Gur-Ari
44
53
0
15 Jun 2020
Learning Diverse and Discriminative Representations via the Principle of
  Maximal Coding Rate Reduction
Learning Diverse and Discriminative Representations via the Principle of Maximal Coding Rate Reduction
Yaodong Yu
Kwan Ho Ryan Chan
Chong You
Chaobing Song
Yi Ma
SSL
31
189
0
15 Jun 2020
Learning Bounds for Risk-sensitive Learning
Learning Bounds for Risk-sensitive Learning
Jaeho Lee
Sejun Park
Jinwoo Shin
25
46
0
15 Jun 2020
Towards Robust Pattern Recognition: A Review
Towards Robust Pattern Recognition: A Review
Xu-Yao Zhang
Cheng-Lin Liu
C. Suen
OOD
HAI
19
103
0
12 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
Meta Transition Adaptation for Robust Deep Learning with Noisy Labels
Meta Transition Adaptation for Robust Deep Learning with Noisy Labels
Jun Shu
Qian Zhao
Zengben Xu
Deyu Meng
NoLa
31
29
0
10 Jun 2020
Probably Approximately Correct Constrained Learning
Probably Approximately Correct Constrained Learning
Luiz F. O. Chamon
Alejandro Ribeiro
22
37
0
09 Jun 2020
Provable tradeoffs in adversarially robust classification
Provable tradeoffs in adversarially robust classification
Yan Sun
Hamed Hassani
David Hong
Alexander Robey
23
53
0
09 Jun 2020
The Curious Case of Convex Neural Networks
The Curious Case of Convex Neural Networks
S. Sivaprasad
Ankur Singh
Naresh Manwani
Vineet Gandhi
46
26
0
09 Jun 2020
Rethinking Importance Weighting for Deep Learning under Distribution
  Shift
Rethinking Importance Weighting for Deep Learning under Distribution Shift
Tongtong Fang
Nan Lu
Gang Niu
Masashi Sugiyama
33
134
0
08 Jun 2020
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