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Implicit Regularization in Deep Learning
v1v2 (latest)

Implicit Regularization in Deep Learning

6 September 2017
Behnam Neyshabur
ArXiv (abs)PDFHTML

Papers citing "Implicit Regularization in Deep Learning"

50 / 108 papers shown
Discriminator-Weighted Offline Imitation Learning from Suboptimal
  Demonstrations
Discriminator-Weighted Offline Imitation Learning from Suboptimal DemonstrationsInternational Conference on Machine Learning (ICML), 2022
Haoran Xu
Xianyuan Zhan
Honglei Yin
Huiling Qin
OffRL
266
98
0
20 Jul 2022
PAC-Bayesian Domain Adaptation Bounds for Multiclass Learners
PAC-Bayesian Domain Adaptation Bounds for Multiclass LearnersConference on Uncertainty in Artificial Intelligence (UAI), 2022
Anthony Sicilia
Katherine Atwell
Malihe Alikhani
Seong Jae Hwang
BDL
218
13
0
12 Jul 2022
Synergy and Symmetry in Deep Learning: Interactions between the Data,
  Model, and Inference Algorithm
Synergy and Symmetry in Deep Learning: Interactions between the Data, Model, and Inference AlgorithmInternational Conference on Machine Learning (ICML), 2022
Lechao Xiao
Jeffrey Pennington
199
11
0
11 Jul 2022
On the Effective Number of Linear Regions in Shallow Univariate ReLU
  Networks: Convergence Guarantees and Implicit Bias
On the Effective Number of Linear Regions in Shallow Univariate ReLU Networks: Convergence Guarantees and Implicit BiasNeural Information Processing Systems (NeurIPS), 2022
Itay Safran
Gal Vardi
Jason D. Lee
MLT
225
24
0
18 May 2022
Policy Gradient Method For Robust Reinforcement Learning
Policy Gradient Method For Robust Reinforcement LearningInternational Conference on Machine Learning (ICML), 2022
Yue Wang
Shaofeng Zou
256
92
0
15 May 2022
AUC Maximization in the Era of Big Data and AI: A Survey
AUC Maximization in the Era of Big Data and AI: A SurveyACM Computing Surveys (ACM CSUR), 2022
Tianbao Yang
Yiming Ying
459
257
0
28 Mar 2022
More Than a Toy: Random Matrix Models Predict How Real-World Neural
  Representations Generalize
More Than a Toy: Random Matrix Models Predict How Real-World Neural Representations GeneralizeInternational Conference on Machine Learning (ICML), 2022
Alexander Wei
Wei Hu
Jacob Steinhardt
246
87
0
11 Mar 2022
Rotationally Equivariant Super-Resolution of Velocity Fields in
  Two-Dimensional Fluids Using Convolutional Neural Networks
Rotationally Equivariant Super-Resolution of Velocity Fields in Two-Dimensional Fluids Using Convolutional Neural NetworksAPL Machine Learning (AML), 2022
Y. Yasuda
R. Onishi
340
7
0
22 Feb 2022
On the Implicit Bias Towards Minimal Depth of Deep Neural Networks
On the Implicit Bias Towards Minimal Depth of Deep Neural Networks
Tomer Galanti
Liane Galanti
Ido Ben-Shaul
326
16
0
18 Feb 2022
A Data-Augmentation Is Worth A Thousand Samples: Exact Quantification
  From Analytical Augmented Sample Moments
A Data-Augmentation Is Worth A Thousand Samples: Exact Quantification From Analytical Augmented Sample Moments
Randall Balestriero
Ishan Misra
Yann LeCun
158
20
0
16 Feb 2022
Controlling the Complexity and Lipschitz Constant improves polynomial
  nets
Controlling the Complexity and Lipschitz Constant improves polynomial netsInternational Conference on Learning Representations (ICLR), 2022
Zhenyu Zhu
Fabian Latorre
Grigorios G. Chrysos
Volkan Cevher
109
12
0
10 Feb 2022
Implicit Regularization in Hierarchical Tensor Factorization and Deep
  Convolutional Neural Networks
Implicit Regularization in Hierarchical Tensor Factorization and Deep Convolutional Neural NetworksInternational Conference on Machine Learning (ICML), 2022
Noam Razin
Asaf Maman
Nadav Cohen
401
33
0
27 Jan 2022
Leveraging Unlabeled Data to Predict Out-of-Distribution Performance
Leveraging Unlabeled Data to Predict Out-of-Distribution PerformanceInternational Conference on Learning Representations (ICLR), 2022
Saurabh Garg
Sivaraman Balakrishnan
Zachary Chase Lipton
Behnam Neyshabur
Hanie Sedghi
OODDOOD
245
156
0
11 Jan 2022
Automated Reinforcement Learning (AutoRL): A Survey and Open Problems
Automated Reinforcement Learning (AutoRL): A Survey and Open ProblemsJournal of Artificial Intelligence Research (JAIR), 2022
Jack Parker-Holder
Raghunandan Rajan
Xingyou Song
André Biedenkapp
Yingjie Miao
...
Vu-Linh Nguyen
Roberto Calandra
Aleksandra Faust
Katharina Eggensperger
Marius Lindauer
AI4CE
361
125
0
11 Jan 2022
Benign Overfitting in Adversarially Robust Linear Classification
Benign Overfitting in Adversarially Robust Linear ClassificationConference on Uncertainty in Artificial Intelligence (UAI), 2021
Jinghui Chen
Yuan Cao
Quanquan Gu
AAMLSILM
202
11
0
31 Dec 2021
Global convergence of ResNets: From finite to infinite width using
  linear parameterization
Global convergence of ResNets: From finite to infinite width using linear parameterization
Raphael Barboni
Gabriel Peyré
Franccois-Xavier Vialard
244
12
0
10 Dec 2021
Sharp Bounds for Federated Averaging (Local SGD) and Continuous
  Perspective
Sharp Bounds for Federated Averaging (Local SGD) and Continuous Perspective
Margalit Glasgow
Honglin Yuan
Tengyu Ma
FedML
199
50
0
05 Nov 2021
Predictive Model Degrees of Freedom in Linear Regression
Predictive Model Degrees of Freedom in Linear Regression
Bo Luan
Yoonkyung Lee
Yunzhang Zhu
175
3
0
29 Jun 2021
Stateful ODE-Nets using Basis Function Expansions
Stateful ODE-Nets using Basis Function ExpansionsNeural Information Processing Systems (NeurIPS), 2021
A. Queiruga
N. Benjamin Erichson
Liam Hodgkinson
Michael W. Mahoney
252
17
0
21 Jun 2021
From inexact optimization to learning via gradient concentration
From inexact optimization to learning via gradient concentrationComputational optimization and applications (COA), 2021
Bernhard Stankewitz
Nicole Mücke
Lorenzo Rosasco
277
5
0
09 Jun 2021
Ghosts in Neural Networks: Existence, Structure and Role of
  Infinite-Dimensional Null Space
Ghosts in Neural Networks: Existence, Structure and Role of Infinite-Dimensional Null Space
Sho Sonoda
Isao Ishikawa
Masahiro Ikeda
BDL
139
9
0
09 Jun 2021
The Dynamics of Gradient Descent for Overparametrized Neural Networks
The Dynamics of Gradient Descent for Overparametrized Neural NetworksConference on Learning for Dynamics & Control (L4DC), 2021
Siddhartha Satpathi
R. Srikant
MLTAI4CE
108
14
0
13 May 2021
Non-Asymptotic Analysis for Two Time-scale TDC with General Smooth
  Function Approximation
Non-Asymptotic Analysis for Two Time-scale TDC with General Smooth Function ApproximationNeural Information Processing Systems (NeurIPS), 2021
Yue Wang
Shaofeng Zou
Yi Zhou
407
11
0
07 Apr 2021
Nonlinear Weighted Directed Acyclic Graph and A Priori Estimates for
  Neural Networks
Nonlinear Weighted Directed Acyclic Graph and A Priori Estimates for Neural NetworksSIAM Journal on Mathematics of Data Science (SIMODS), 2021
Yuqing Li
Yaoyu Zhang
Chao Ma
CML
243
2
0
30 Mar 2021
Consensus Control for Decentralized Deep Learning
Consensus Control for Decentralized Deep LearningInternational Conference on Machine Learning (ICML), 2021
Lingjing Kong
Tao Lin
Anastasia Koloskova
Martin Jaggi
Sebastian U. Stich
231
89
0
09 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
198
56
0
14 Dec 2020
On Computability, Learnability and Extractability of Finite State
  Machines from Recurrent Neural Networks
On Computability, Learnability and Extractability of Finite State Machines from Recurrent Neural Networks
Reda Marzouk
166
2
0
10 Sep 2020
Implicit Bias in Deep Linear Classification: Initialization Scale vs
  Training Accuracy
Implicit Bias in Deep Linear Classification: Initialization Scale vs Training AccuracyNeural Information Processing Systems (NeurIPS), 2020
E. Moroshko
Suriya Gunasekar
Blake E. Woodworth
Jason D. Lee
Nathan Srebro
Daniel Soudry
205
89
0
13 Jul 2020
The Global Landscape of Neural Networks: An Overview
The Global Landscape of Neural Networks: An Overview
Tian Ding
Dawei Li
Shiyu Liang
Tian Ding
R. Srikant
214
93
0
02 Jul 2020
Extrapolation for Large-batch Training in Deep Learning
Extrapolation for Large-batch Training in Deep LearningInternational Conference on Machine Learning (ICML), 2020
Tao Lin
Lingjing Kong
Sebastian U. Stich
Martin Jaggi
258
40
0
10 Jun 2020
An Empirical Analysis of the Impact of Data Augmentation on Knowledge
  Distillation
An Empirical Analysis of the Impact of Data Augmentation on Knowledge Distillation
Deepan Das
Haley Massa
Abhimanyu Kulkarni
Theodoros Rekatsinas
190
19
0
06 Jun 2020
Statistical Guarantees for Regularized Neural Networks
Statistical Guarantees for Regularized Neural NetworksNeural Networks (NN), 2020
Mahsa Taheri
Fang Xie
Johannes Lederer
267
41
0
30 May 2020
Implicit Regularization in Deep Learning May Not Be Explainable by Norms
Implicit Regularization in Deep Learning May Not Be Explainable by Norms
Noam Razin
Nadav Cohen
298
163
0
13 May 2020
On the Benefits of Invariance in Neural Networks
On the Benefits of Invariance in Neural Networks
Clare Lyle
Mark van der Wilk
Marta Z. Kwiatkowska
Y. Gal
Benjamin Bloem-Reddy
OODBDL
277
99
0
01 May 2020
Finite-sample Analysis of Interpolating Linear Classifiers in the
  Overparameterized Regime
Finite-sample Analysis of Interpolating Linear Classifiers in the Overparameterized RegimeJournal of machine learning research (JMLR), 2020
Niladri S. Chatterji
Philip M. Long
233
114
0
25 Apr 2020
Robust and On-the-fly Dataset Denoising for Image Classification
Robust and On-the-fly Dataset Denoising for Image ClassificationEuropean Conference on Computer Vision (ECCV), 2020
Jiaming Song
Lunjia Hu
Michael Auli
Yann N. Dauphin
Tengyu Ma
NoLaOOD
178
13
0
24 Mar 2020
Can Implicit Bias Explain Generalization? Stochastic Convex Optimization
  as a Case Study
Can Implicit Bias Explain Generalization? Stochastic Convex Optimization as a Case StudyNeural Information Processing Systems (NeurIPS), 2020
Assaf Dauber
M. Feder
Tomer Koren
Roi Livni
221
25
0
13 Mar 2020
Implicit Geometric Regularization for Learning Shapes
Implicit Geometric Regularization for Learning ShapesInternational Conference on Machine Learning (ICML), 2020
Amos Gropp
Lior Yariv
Niv Haim
Matan Atzmon
Y. Lipman
AI4CE
415
962
0
24 Feb 2020
The Break-Even Point on Optimization Trajectories of Deep Neural
  Networks
The Break-Even Point on Optimization Trajectories of Deep Neural NetworksInternational Conference on Learning Representations (ICLR), 2020
Stanislaw Jastrzebski
Maciej Szymczak
Stanislav Fort
Devansh Arpit
Jacek Tabor
Dong Wang
Krzysztof J. Geras
237
183
0
21 Feb 2020
Sideways: Depth-Parallel Training of Video Models
Sideways: Depth-Parallel Training of Video ModelsComputer Vision and Pattern Recognition (CVPR), 2020
Mateusz Malinowski
G. Swirszcz
João Carreira
Viorica Patraucean
MDE
345
15
0
17 Jan 2020
On the Bias-Variance Tradeoff: Textbooks Need an Update
On the Bias-Variance Tradeoff: Textbooks Need an Update
Brady Neal
99
20
0
17 Dec 2019
Exact expressions for double descent and implicit regularization via
  surrogate random design
Exact expressions for double descent and implicit regularization via surrogate random designNeural Information Processing Systems (NeurIPS), 2019
Michal Derezinski
Feynman T. Liang
Michael W. Mahoney
329
79
0
10 Dec 2019
Observational Overfitting in Reinforcement Learning
Observational Overfitting in Reinforcement LearningInternational Conference on Learning Representations (ICLR), 2019
Xingyou Song
Yiding Jiang
Stephen Tu
Yilun Du
Behnam Neyshabur
OffRL
260
147
0
06 Dec 2019
How Implicit Regularization of ReLU Neural Networks Characterizes the
  Learned Function -- Part I: the 1-D Case of Two Layers with Random First
  Layer
How Implicit Regularization of ReLU Neural Networks Characterizes the Learned Function -- Part I: the 1-D Case of Two Layers with Random First Layer
Jakob Heiss
Josef Teichmann
Hanna Wutte
MLT
230
5
0
07 Nov 2019
Implicit competitive regularization in GANs
Implicit competitive regularization in GANsInternational Conference on Machine Learning (ICML), 2019
Florian Schäfer
Hongkai Zheng
Anima Anandkumar
GAN
256
34
0
13 Oct 2019
Understanding Adversarial Robustness Through Loss Landscape Geometries
Understanding Adversarial Robustness Through Loss Landscape Geometries
Vinay Uday Prabhu
Dian Ang Yap
Joyce Xu
John Whaley
AAML
119
19
0
22 Jul 2019
Bad Global Minima Exist and SGD Can Reach Them
Bad Global Minima Exist and SGD Can Reach ThemNeural Information Processing Systems (NeurIPS), 2019
Shengchao Liu
Dimitris Papailiopoulos
D. Achlioptas
190
83
0
06 Jun 2019
Implicit Regularization of Discrete Gradient Dynamics in Linear Neural
  Networks
Implicit Regularization of Discrete Gradient Dynamics in Linear Neural NetworksNeural Information Processing Systems (NeurIPS), 2019
Gauthier Gidel
Francis R. Bach
Damien Scieur
AI4CE
185
168
0
30 Apr 2019
Deep Learning for Inverse Problems: Bounds and Regularizers
Deep Learning for Inverse Problems: Bounds and Regularizers
Jaweria Amjad
Zhaoyang Lyu
M. Rodrigues
84
4
0
31 Jan 2019
On the potential for open-endedness in neural networks
On the potential for open-endedness in neural networks
N. Guttenberg
N. Virgo
A. Penn
136
11
0
12 Dec 2018
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