Jeremy Bernstein

32 papers A* 7Journal 21Unranked 4

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	Modular Duality in Deep Learning. ICML Jeremy Bernstein, Laker Newhouse
2025	J	`jnl`	Training Transformers with Enforced Lipschitz Constants. CoRR Laker Newhouse, R. Preston Hess, Franz Cesista, Andrii Zahorodnii, Jeremy Bernstein, Phillip Isola
2024	J	`jnl`	Devising and Detecting Phishing Emails Using Large Language Models. IEEE Access Fredrik Heiding, Bruce Schneier, Arun Vishwanath, Jeremy Bernstein, Peter S. Park
2024	J	`jnl`	Modular Duality in Deep Learning. CoRR Jeremy Bernstein, Laker Newhouse
2024	J	`jnl`	Old Optimizer, New Norm: An Anthology. CoRR Jeremy Bernstein, Laker Newhouse
2024	A*	`conf`	Scalable Optimization in the Modular Norm. NeurIPS Tim Large, Yang Liu, Jacob Huh, Hyojin Bahng, Phillip Isola, Jeremy Bernstein
2024	J	`jnl`	Scalable Optimization in the Modular Norm. CoRR Tim Large, Yang Liu, Minyoung Huh, Hyojin Bahng, Phillip Isola, Jeremy Bernstein
2024	J	`jnl`	Training Neural Networks from Scratch with Parallel Low-Rank Adapters. CoRR Minyoung Huh, Brian Cheung, Jeremy Bernstein, Phillip Isola, Pulkit Agrawal
2023	J	`jnl`	A Spectral Condition for Feature Learning. CoRR Greg Yang, James B. Simon, Jeremy Bernstein
2023	J	`jnl`	Automatic Gradient Descent: Deep Learning without Hyperparameters. CoRR Jeremy Bernstein, Chris Mingard, Kevin Huang, Navid Azizan, Yisong Yue
2023	J	`jnl`	Devising and Detecting Phishing: Large Language Models vs. Smaller Human Models. CoRR Fredrik Heiding, Bruce Schneier, Arun Vishwanath, Jeremy Bernstein
2023	J	`jnl`	SketchOGD: Memory-Efficient Continual Learning. CoRR Benjamin Wright, Youngjae Min, Jeremy Bernstein, Navid Azizan
2022	J	`jnl`	Investigating Generalization by Controlling Normalized Margin. CoRR Alexander R. Farhang, Jeremy Bernstein, Kushal Tirumala, Yang Liu, Yisong Yue
2022	J	`jnl`	Optimisation & Generalisation in Networks of Neurons. CoRR Jeremy Bernstein
2021	J	`jnl`	Computing the Information Content of Trained Neural Networks. CoRR Jeremy Bernstein, Yisong Yue
2021	A*	`conf`	Fine-Grained System Identification of Nonlinear Neural Circuits. KDD Dawna Bagherian, James Gornet, Jeremy Bernstein, Yu-Li Ni, Yisong Yue, Markus Meister
2021	J	`jnl`	Fine-Grained System Identification of Nonlinear Neural Circuits. CoRR Dawna Bagherian, James Gornet, Jeremy Bernstein, Yu-Li Ni, Yisong Yue, Markus Meister
2021	A*	`conf`	Learning by Turning: Neural Architecture Aware Optimisation. ICML Yang Liu, Jeremy Bernstein, Markus Meister, Yisong Yue
2021	J	`jnl`	Learning by Turning: Neural Architecture Aware Optimisation. CoRR Yang Liu, Jeremy Bernstein, Markus Meister, Yisong Yue
2021	J	`jnl`	On the Implicit Biases of Architecture & Gradient Descent. CoRR Jeremy Bernstein, Yisong Yue
2020	A*	`conf`	Learning compositional functions via multiplicative weight updates. NeurIPS Jeremy Bernstein, Jiawei Zhao, Markus Meister, Ming-Yu Liu, Anima Anandkumar, Yisong Yue
2020	J	`jnl`	Learning compositional functions via multiplicative weight updates. CoRR Jeremy Bernstein, Jiawei Zhao, Markus Meister, Ming-Yu Liu, Anima Anandkumar, Yisong Yue
2020	A*	`conf`	On the distance between two neural networks and the stability of learning. NeurIPS Jeremy Bernstein, Arash Vahdat, Yisong Yue, Ming-Yu Liu
2020	J	`jnl`	On the distance between two neural networks and the stability of learning. CoRR Jeremy Bernstein, Arash Vahdat, Yisong Yue, Ming-Yu Liu
2019	—	`conf`	signSGD with Majority Vote is Communication Efficient and Fault Tolerant. ICLR (Poster) Jeremy Bernstein, Jiawei Zhao, Kamyar Azizzadenesheli, Anima Anandkumar
2018	—	`conf`	Compression by the signs: distributed learning is a two-way street. ICLR (Workshop) Jeremy Bernstein, Yu-Xiang Wang, Kamyar Azizzadenesheli, Anima Anandkumar
2018	A*	`conf`	SIGNSGD: Compressed Optimisation for Non-Convex Problems. ICML Jeremy Bernstein, Yu-Xiang Wang, Kamyar Azizzadenesheli, Animashree Anandkumar
2018	—	`conf`	Stochastic Activation Pruning for Robust Adversarial Defense. ICLR (Poster) Guneet S. Dhillon, Kamyar Azizzadenesheli, Zachary C. Lipton, Jeremy Bernstein, Jean Kossaifi, Aran Khanna, Animashree Anandkumar
2018	J	`jnl`	Stochastic Activation Pruning for Robust Adversarial Defense. CoRR Guneet S. Dhillon, Kamyar Azizzadenesheli, Zachary C. Lipton, Jeremy Bernstein, Jean Kossaifi, Aran Khanna, Anima Anandkumar
2018	J	`jnl`	signSGD with Majority Vote is Communication Efficient And Byzantine Fault Tolerant. CoRR Jeremy Bernstein, Jiawei Zhao, Kamyar Azizzadenesheli, Anima Anandkumar
2018	J	`jnl`	signSGD: compressed optimisation for non-convex problems. CoRR Jeremy Bernstein, Yu-Xiang Wang, Kamyar Azizzadenesheli, Anima Anandkumar
2017	—	`conf`	Markov Transitions between Attractor States in a Recurrent Neural Network. AAAI Spring Symposia Jeremy Bernstein, Ishita Dasgupta, David Rolnick, Haim Sompolinsky