← Authors

Behnam Neyshabur

34 papers · 2013–2023 · 4 conferences · across top CS/AI conferences

Achievements

🌍 Conference Polyglot (4) πŸ—ΊοΈ Taxonomy Completionist (36) 🌈 Renaissance Researcher (8) 🐝 Cross-Pollinator (7) πŸŒ‰ Interdisciplinary Bridge 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird πŸƒ Academic Marathon (10) 🌟 Keyword Trendsetter Combo (4) πŸ† Keyword Champion 🧬 Topic Evolution πŸ‘‘ Triple Crown ⚑ Prolific Year (9) πŸ“ˆ Trend Setter πŸ—ƒοΈ Keyword Collector (90) πŸ’Ž Century Club (34) ❓ The Questioner (3) πŸ”₯ Unstoppable (9) πŸš€ Conference Pioneer

Conferences

ICLR (16) NIPS (13) ICML (3) COLT (2)

Top co-authors

Hanie Sedghi (7) Nati Srebro (6) Srinadh Bhojanapalli (5) Ethan Dyer (4) Yuhuai Wu (4) Nathan Srebro (4) Anders Andreassen (3) Ruslan Salakhutdinov (3) Guy Gur-Ari (3) Vinay Ramasesh (2)

Keywords

language modeling (2) generalization bound (2) deep neural network (2) gradient descent (2) stochastic gradient descent (2) image classification (2) recurrent neural network (2) matrix factorization (2) metric learning (1) mathematical reasoning (1) neural network compression (1) in-context learning (1) neural machine translation (1) out-of-distribution generalization (1) similarity search (1) loss landscape (1) neural network optimization (1) transfer learning (1) deep learning (1) neural architecture search (1)

Papers

Long Range Language Modeling via Gated State Spaces ICLR 2023
REPAIR: REnormalizing Permuted Activations for Interpolation Repair ICLR 2023
Solving Quantitative Reasoning Problems with Language Models NIPS 2022
A Loss Curvature Perspective on Training Instabilities of Deep Learning Models ICLR 2022
Data Scaling Laws in NMT: The Effect of Noise and Architecture ICML 2022
Revisiting Neural Scaling Laws in Language and Vision NIPS 2022
Block-Recurrent Transformers NIPS 2022
Exploring Length Generalization in Large Language Models NIPS 2022
The Role of Permutation Invariance in Linear Mode Connectivity of Neural Networks ICLR 2022
Leveraging unlabeled data to predict out-of-distribution performance ICLR 2022
Exploring the Limits of Large Scale Pre-training ICLR 2022
Understanding the failure modes of out-of-distribution generalization ICLR 2021
When Do Curricula Work? ICLR 2021
The Deep Bootstrap Framework: Good Online Learners are Good Offline Generalizers ICLR 2021
Sharpness-aware Minimization for Efficiently Improving Generalization ICLR 2021
Are wider nets better given the same number of parameters? ICLR 2021
Deep Learning Through the Lens of Example Difficulty NIPS 2021
Extreme Memorization via Scale of Initialization ICLR 2021
The intriguing role of module criticality in the generalization of deep networks ICLR 2020
What is being transferred in transfer learning? NIPS 2020
Towards Learning Convolutions from Scratch NIPS 2020
Observational Overfitting in Reinforcement Learning ICLR 2020
The role of over-parametrization in generalization of neural networks ICLR 2019
A PAC-Bayesian Approach to Spectrally-Normalized Margin Bounds for Neural Networks ICLR 2018
Stronger Generalization Bounds for Deep Nets via a Compression Approach ICML 2018
Exploring Generalization in Deep Learning NIPS 2017
Corralling a Band of Bandit Algorithms COLT 2017
Implicit Regularization in Matrix Factorization NIPS 2017
Global Optimality of Local Search for Low Rank Matrix Recovery NIPS 2016
Path-Normalized Optimization of Recurrent Neural Networks with ReLU Activations NIPS 2016
Path-SGD: Path-Normalized Optimization in Deep Neural Networks NIPS 2015
Norm-Based Capacity Control in Neural Networks COLT 2015
On Symmetric and Asymmetric LSHs for Inner Product Search ICML 2015
The Power of Asymmetry in Binary Hashing NIPS 2013