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Jonathan Hayase
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Journal Articles
- 2023
- [j1]Shuaiqi Wang, Jonathan Hayase, Giulia Fanti, Sewoong Oh:
Towards a Defense Against Federated Backdoor Attacks Under Continuous Training. Trans. Mach. Learn. Res. 2023 (2023)
Conference and Workshop Papers
- 2024
- [c9]Gavin Brown, Jonathan Hayase, Samuel B. Hopkins, Weihao Kong, Xiyang Liu, Sewoong Oh, Juan C. Perdomo, Adam Smith:
Insufficient Statistics Perturbation: Stable Estimators for Private Least Squares Extended Abstract. COLT 2024: 750-751 - [c8]Nicholas Carlini, Daniel Paleka, Krishnamurthy Dj Dvijotham, Thomas Steinke, Jonathan Hayase, A. Feder Cooper, Katherine Lee, Matthew Jagielski, Milad Nasr, Arthur Conmy, Eric Wallace, David Rolnick, Florian Tramèr:
Stealing part of a production language model. ICML 2024 - 2023
- [c7]Samuel K. Ainsworth, Jonathan Hayase, Siddhartha S. Srinivasa:
Git Re-Basin: Merging Models modulo Permutation Symmetries. ICLR 2023 - [c6]Jonathan Hayase, Sewoong Oh:
Few-shot Backdoor Attacks via Neural Tangent Kernels. ICLR 2023 - [c5]Samir Yitzhak Gadre, Gabriel Ilharco, Alex Fang, Jonathan Hayase, Georgios Smyrnis, Thao Nguyen, Ryan Marten, Mitchell Wortsman, Dhruba Ghosh, Jieyu Zhang, Eyal Orgad, Rahim Entezari, Giannis Daras, Sarah M. Pratt, Vivek Ramanujan, Yonatan Bitton, Kalyani Marathe, Stephen Mussmann, Richard Vencu, Mehdi Cherti, Ranjay Krishna, Pang Wei Koh, Olga Saukh, Alexander J. Ratner, Shuran Song, Hannaneh Hajishirzi, Ali Farhadi, Romain Beaumont, Sewoong Oh, Alex Dimakis, Jenia Jitsev, Yair Carmon, Vaishaal Shankar, Ludwig Schmidt:
DataComp: In search of the next generation of multimodal datasets. NeurIPS 2023 - [c4]Rishi D. Jha, Jonathan Hayase, Sewoong Oh:
Label Poisoning is All You Need. NeurIPS 2023 - 2022
- [c3]Matt Jordan, Jonathan Hayase, Alex Dimakis, Sewoong Oh:
Zonotope Domains for Lagrangian Neural Network Verification. NeurIPS 2022 - 2021
- [c2]Jonathan Hayase, Weihao Kong, Raghav Somani, Sewoong Oh:
Defense against backdoor attacks via robust covariance estimation. ICML 2021: 4129-4139 - 2019
- [c1]George D. Montañez, Jonathan Hayase, Julius Lauw, Dominique Macias, Akshay Trikha, Julia Vendemiatti:
The Futility of Bias-Free Learning and Search. Australasian Conference on Artificial Intelligence 2019: 277-288
Informal and Other Publications
- 2024
- [i15]Jonathan Hayase, Ema Borevkovic, Nicholas Carlini, Florian Tramèr, Milad Nasr:
Query-Based Adversarial Prompt Generation. CoRR abs/2402.12329 (2024) - [i14]Nicholas Carlini, Daniel Paleka, Krishnamurthy (Dj) Dvijotham, Thomas Steinke, Jonathan Hayase, A. Feder Cooper, Katherine Lee, Matthew Jagielski, Milad Nasr, Arthur Conmy, Eric Wallace, David Rolnick, Florian Tramèr:
Stealing Part of a Production Language Model. CoRR abs/2403.06634 (2024) - [i13]Gavin Brown, Jonathan Hayase, Samuel B. Hopkins, Weihao Kong, Xiyang Liu, Sewoong Oh, Juan C. Perdomo, Adam Smith:
Insufficient Statistics Perturbation: Stable Estimators for Private Least Squares. CoRR abs/2404.15409 (2024) - [i12]Anshul Nasery, Jonathan Hayase, Pang Wei Koh, Sewoong Oh:
PLeaS - Merging Models with Permutations and Least Squares. CoRR abs/2407.02447 (2024) - [i11]Jonathan Hayase, Alisa Liu, Yejin Choi, Sewoong Oh, Noah A. Smith:
Data Mixture Inference: What do BPE Tokenizers Reveal about their Training Data? CoRR abs/2407.16607 (2024) - [i10]Forest Kobayashi, Jonathan Hayase, Young-Heon Kim:
Monge-Kantorovich Fitting With Sobolev Budgets. CoRR abs/2409.16541 (2024) - 2023
- [i9]Samir Yitzhak Gadre, Gabriel Ilharco, Alex Fang, Jonathan Hayase, Georgios Smyrnis, Thao Nguyen, Ryan Marten, Mitchell Wortsman, Dhruba Ghosh, Jieyu Zhang, Eyal Orgad, Rahim Entezari, Giannis Daras, Sarah M. Pratt, Vivek Ramanujan, Yonatan Bitton, Kalyani Marathe, Stephen Mussmann, Richard Vencu, Mehdi Cherti, Ranjay Krishna, Pang Wei Koh, Olga Saukh, Alexander Ratner, Shuran Song, Hannaneh Hajishirzi, Ali Farhadi, Romain Beaumont, Sewoong Oh, Alex Dimakis, Jenia Jitsev, Yair Carmon, Vaishaal Shankar, Ludwig Schmidt:
DataComp: In search of the next generation of multimodal datasets. CoRR abs/2304.14108 (2023) - [i8]Rishi D. Jha, Jonathan Hayase, Sewoong Oh:
Label Poisoning is All You Need. CoRR abs/2310.18933 (2023) - [i7]Milad Nasr, Nicholas Carlini, Jonathan Hayase, Matthew Jagielski, A. Feder Cooper, Daphne Ippolito, Christopher A. Choquette-Choo, Eric Wallace, Florian Tramèr, Katherine Lee:
Scalable Extraction of Training Data from (Production) Language Models. CoRR abs/2311.17035 (2023) - 2022
- [i6]Shuaiqi Wang, Jonathan Hayase, Giulia Fanti, Sewoong Oh:
Towards a Defense against Backdoor Attacks in Continual Federated Learning. CoRR abs/2205.11736 (2022) - [i5]Samuel K. Ainsworth, Jonathan Hayase, Siddhartha S. Srinivasa:
Git Re-Basin: Merging Models modulo Permutation Symmetries. CoRR abs/2209.04836 (2022) - [i4]Jonathan Hayase, Sewoong Oh:
Few-shot Backdoor Attacks via Neural Tangent Kernels. CoRR abs/2210.05929 (2022) - [i3]Matt Jordan, Jonathan Hayase, Alexandros G. Dimakis, Sewoong Oh:
Zonotope Domains for Lagrangian Neural Network Verification. CoRR abs/2210.08069 (2022) - 2021
- [i2]Jonathan Hayase, Weihao Kong, Raghav Somani, Sewoong Oh:
SPECTRE: Defending Against Backdoor Attacks Using Robust Statistics. CoRR abs/2104.11315 (2021) - 2019
- [i1]George D. Montañez, Jonathan Hayase, Julius Lauw, Dominique Macias, Akshay Trikha, Julia Vendemiatti:
The Futility of Bias-Free Learning and Search. CoRR abs/1907.06010 (2019)
Coauthor Index
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