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Jeremy Bernstein
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2020 – today
- 2024
- [j1]Fredrik Heiding
, Bruce Schneier
Devising and Detecting Phishing Emails Using Large Language Models. IEEE Access 12: 42131-42146 (2024) - [i19]Minyoung Huh, Brian Cheung, Jeremy Bernstein, Phillip Isola, Pulkit Agrawal:
Training Neural Networks from Scratch with Parallel Low-Rank Adapters. CoRR abs/2402.16828 (2024) - [i18]Tim Large, Yang Liu, Minyoung Huh, Hyojin Bahng, Phillip Isola, Jeremy Bernstein:
Scalable Optimization in the Modular Norm. CoRR abs/2405.14813 (2024) - [i17]Jeremy Bernstein, Laker Newhouse:
Old Optimizer, New Norm: An Anthology. CoRR abs/2409.20325 (2024) - [i16]Jeremy Bernstein, Laker Newhouse:
Modular Duality in Deep Learning. CoRR abs/2410.21265 (2024) - 2023
- [i15]Jeremy Bernstein, Chris Mingard, Kevin Huang, Navid Azizan
Automatic Gradient Descent: Deep Learning without Hyperparameters. CoRR abs/2304.05187 (2023) - [i14]Benjamin Wright, Youngjae Min, Jeremy Bernstein, Navid Azizan:
SketchOGD: Memory-Efficient Continual Learning. CoRR abs/2305.16424 (2023) - [i13]Fredrik Heiding, Bruce Schneier, Arun Vishwanath, Jeremy Bernstein:
Devising and Detecting Phishing: Large Language Models vs. Smaller Human Models. CoRR abs/2308.12287 (2023) - [i12]Greg Yang, James B. Simon, Jeremy Bernstein:
A Spectral Condition for Feature Learning. CoRR abs/2310.17813 (2023) - 2022
- [c10]Alexander R. Farhang, Jeremy D. Bernstein, Kushal Tirumala, Yang Liu, Yisong Yue:
Investigating Generalization by Controlling Normalized Margin. ICML 2022: 6324-6336 - [i11]Alexander R. Farhang
Investigating Generalization by Controlling Normalized Margin. CoRR abs/2205.03940 (2022) - [i10]Jeremy Bernstein:
Optimisation & Generalisation in Networks of Neurons. CoRR abs/2210.10101 (2022) - 2021
- [c9]Yang Liu, Jeremy Bernstein, Markus Meister, Yisong Yue:
Learning by Turning: Neural Architecture Aware Optimisation. ICML 2021: 6748-6758 - [c8]Dawna Bagherian, James Gornet
Fine-Grained System Identification of Nonlinear Neural Circuits. KDD 2021: 14-24 - [i9]Yang Liu, Jeremy Bernstein, Markus Meister, Yisong Yue:
Learning by Turning: Neural Architecture Aware Optimisation. CoRR abs/2102.07227 (2021) - [i8]Jeremy Bernstein, Yisong Yue:
Computing the Information Content of Trained Neural Networks. CoRR abs/2103.01045 (2021) - [i7]Dawna Bagherian, James Gornet, Jeremy Bernstein, Yu-Li Ni, Yisong Yue, Markus Meister:
Fine-Grained System Identification of Nonlinear Neural Circuits. CoRR abs/2106.05400 (2021) - [i6]Jeremy Bernstein, Yisong Yue:
On the Implicit Biases of Architecture & Gradient Descent. CoRR abs/2110.04274 (2021) - 2020
- [c7]Jeremy Bernstein, Arash Vahdat, Yisong Yue, Ming-Yu Liu:
On the distance between two neural networks and the stability of learning. NeurIPS 2020 - [c6]Jeremy Bernstein, Jiawei Zhao, Markus Meister, Ming-Yu Liu, Anima Anandkumar, Yisong Yue:
Learning compositional functions via multiplicative weight updates. NeurIPS 2020 - [i5]Jeremy Bernstein, Arash Vahdat, Yisong Yue, Ming-Yu Liu:
On the distance between two neural networks and the stability of learning. CoRR abs/2002.03432 (2020) - [i4]Jeremy Bernstein, Jiawei Zhao, Markus Meister, Ming-Yu Liu, Anima Anandkumar, Yisong Yue:
Learning compositional functions via multiplicative weight updates. CoRR abs/2006.14560 (2020)
2010 – 2019
- 2019
- [c5]Jeremy Bernstein, Jiawei Zhao, Kamyar Azizzadenesheli, Anima Anandkumar:
signSGD with Majority Vote is Communication Efficient and Fault Tolerant. ICLR (Poster) 2019 - 2018
- [c4]Jeremy Bernstein, Yu-Xiang Wang, Kamyar Azizzadenesheli, Anima Anandkumar:
Compression by the signs: distributed learning is a two-way street. ICLR (Workshop) 2018 - [c3]Guneet S. Dhillon, Kamyar Azizzadenesheli, Zachary C. Lipton, Jeremy Bernstein, Jean Kossaifi, Aran Khanna, Animashree Anandkumar:
Stochastic Activation Pruning for Robust Adversarial Defense. ICLR (Poster) 2018 - [c2]Jeremy Bernstein, Yu-Xiang Wang, Kamyar Azizzadenesheli, Animashree Anandkumar:
SIGNSGD: Compressed Optimisation for Non-Convex Problems. ICML 2018: 559-568 - [i3]Jeremy Bernstein, Yu-Xiang Wang, Kamyar Azizzadenesheli, Anima Anandkumar:
signSGD: compressed optimisation for non-convex problems. CoRR abs/1802.04434 (2018) - [i2]Guneet S. Dhillon, Kamyar Azizzadenesheli, Zachary C. Lipton, Jeremy Bernstein, Jean Kossaifi, Aran Khanna, Anima Anandkumar:
Stochastic Activation Pruning for Robust Adversarial Defense. CoRR abs/1803.01442 (2018) - [i1]Jeremy Bernstein, Jiawei Zhao, Kamyar Azizzadenesheli, Anima Anandkumar:
signSGD with Majority Vote is Communication Efficient And Byzantine Fault Tolerant. CoRR abs/1810.05291 (2018) - 2017
- [c1]Jeremy Bernstein, Ishita Dasgupta, David Rolnick, Haim Sompolinsky:
Markov Transitions between Attractor States in a Recurrent Neural Network. AAAI Spring Symposia 2017
Coauthor Index
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