Behnam Neyshabur - AI Profile

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Research Interests
Machine Learning, Statistical Learning Theory, Optimization
• Primary area: Optimization and Generalization in Deep Learning.
• Secondary areas: Computational Biology, Binary Hashing, Matrix Factorization

Research Interests

Papers41 papers

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Sharpness-Aware Minimization for Efficiently Improving Generalization

Pierre Foret, Ariel Kleiner,Hossein Mobahi,Behnam Neyshabur

ICLR, (2021)

EIBibtex

Are wider nets better given the same number of parameters

Anna Golubeva,Guy Gur-Ari,Behnam Neyshabur

ICLR, (2021)

EIBibtex

The Bootstrap Framework: Generalization Through the Lens of Online Optimization

Preetum Nakkiran,Behnam Neyshabur,Hanie Sedghi

international conference on learning representations, (2021)

Bibtex

The Deep Bootstrap Framework: Good Online Learners are Good Offline Generalizers

Preetum Nakkiran,Behnam Neyshabur,Hanie Sedghi

ICLR, (2021)

EIBibtex

When Do Curricula Work

Xiaoxia Wu, Ethan Dyer,Behnam Neyshabur

ICLR, (2021)

EIBibtex

Understanding the Failure Modes of Out-of-Distribution Generalization

Vaishnavh Nagarajan, Anders Andreassen,Behnam Neyshabur

ICLR, (2021)

EIBibtex

Extreme Memorization via Scale of Initialization

Harsh Mehta,Ashok Cutkosky,Behnam Neyshabur

ICLR, (2021)

EIBibtex

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

Niladri Chatterji,Behnam Neyshabur,Hanie Sedghi

ICLR, (2020)

Cited by17EIBibtex

Are wider nets better given the same number of parameters

Anna Golubeva,Behnam Neyshabur,Guy Gur-Ari

Bibtex

What is being transferred in transfer learning

Behnam Neyshabur,Hanie Sedghi,Chiyuan Zhang

NIPS 2020, (2020)

Cited by37EIBibtex

Towards Learning Convolutions from Scratch

Behnam Neyshabur

NIPS 2020, (2020)

Cited by16EIBibtex

Observational Overfitting in Reinforcement Learning

Xingyou Song, Yiding Jiang, Stephen Tu,Yilun Du,Behnam Neyshabur

ICLR, (2020)

EIBibtex

Fantastic Generalization Measures and Where to Find Them

Jiang Yiding,Neyshabur Behnam,Mobahi Hossein,Krishnan Dilip,Bengio Samy

ICLR, (2020)

Cited by117EIBibtex

Observational Overfitting in Reinforcement Learning

Xingyou Song, Yiding Jiang,Yilun Du,Behnam Neyshabur

international conference on learning representations, (2020)

Bibtex

NeurIPS 2020 Competition: Predicting Generalization in Deep Learning

Yiding Jiang, Pierre Foret, Scott Yak,Daniel M. Roy,Hossein Mobahi,Gintare Karolina Dziugaite,Samy Bengio,Suriya Gunasekar, Isabelle Guyon,Behnam Neyshabur

Cited by2Bibtex

The role of over-parametrization in generalization of neural networks

Behnam Neyshabur,Zhiyuan Li,Srinadh Bhojanapalli,Yann LeCun,Nathan Srebro

ICLR, (2019)

Cited by122EIBibtex

Predicting protein-protein interactions through sequence-based deep learning

Somaye Hashemifar,Behnam Neyshabur,Aly A. Khan,Jinbo Xu

BIOINFORMATICS, no. 17 (2018): 802-810

Cited by66EIWOSBibtex

A PAC-Bayesian Approach to Spectrally-Normalized Margin Bounds for Neural Networks

Behnam Neyshabur,Srinadh Bhojanapalli,Nathan Srebro

international conference on learning representations, (2018)

Bibtex

A PAC-Bayesian Approach to Spectrally-Normalized Margin Bounds for Neural Networks

Behnam Neyshabur,Srinadh Bhojanapalli,David McAllester,Nathan Srebro

ICLR, (2018)

Cited by328EIBibtex

Implicit Regularization in Matrix Factorization

Suriya Gunasekar,Blake E. Woodworth,Srinadh Bhojanapalli,Behnam Neyshabur,Nathan Srebro

information theory and applications, (2018)

Cited by216EIBibtex

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Behnam NeyshaburUnknow

Papers41 papers