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Michael I. Jordan
- > Home > Persons > Michael I. Jordan
Publications
- 2024
- [i334]Banghua Zhu, Michael I. Jordan, Jiantao Jiao:
Iterative Data Smoothing: Mitigating Reward Overfitting and Overoptimization in RLHF. CoRR abs/2401.16335 (2024) - 2023
- [c391]Banghua Zhu, Lun Wang, Qi Pang, Shuai Wang, Jiantao Jiao, Dawn Song, Michael I. Jordan:
Byzantine-Robust Federated Learning with Optimal Statistical Rates. AISTATS 2023: 3151-3178 - [c381]Geng Zhao, Banghua Zhu, Jiantao Jiao, Michael I. Jordan:
Online Learning in Stackelberg Games with an Omniscient Follower. ICML 2023: 42304-42316 - [c380]Banghua Zhu, Michael I. Jordan, Jiantao Jiao:
Principled Reinforcement Learning with Human Feedback from Pairwise or K-wise Comparisons. ICML 2023: 43037-43067 - [c373]Banghua Zhu, Ying Sheng, Lianmin Zheng, Clark W. Barrett, Michael I. Jordan, Jiantao Jiao:
Towards Optimal Caching and Model Selection for Large Model Inference. NeurIPS 2023 - [c372]Banghua Zhu, Mingyu Ding, Philip L. Jacobson, Ming Wu, Wei Zhan, Michael I. Jordan, Jiantao Jiao:
Doubly-Robust Self-Training. NeurIPS 2023 - [c370]Banghua Zhu, Stephen Bates, Zhuoran Yang, Yixin Wang, Jiantao Jiao, Michael I. Jordan:
The Sample Complexity of Online Contract Design. EC 2023: 1188 - [i321]Banghua Zhu, Jiantao Jiao, Michael I. Jordan:
Principled Reinforcement Learning with Human Feedback from Pairwise or K-wise Comparisons. CoRR abs/2301.11270 (2023) - [i320]Geng Zhao, Banghua Zhu, Jiantao Jiao, Michael I. Jordan:
Online Learning in Stackelberg Games with an Omniscient Follower. CoRR abs/2301.11518 (2023) - [i314]Banghua Zhu, Sai Praneeth Karimireddy, Jiantao Jiao, Michael I. Jordan:
Online Learning in a Creator Economy. CoRR abs/2305.11381 (2023) - [i311]Banghua Zhu, Mingyu Ding, Philip L. Jacobson, Ming Wu, Wei Zhan, Michael I. Jordan, Jiantao Jiao:
Doubly Robust Self-Training. CoRR abs/2306.00265 (2023) - [i310]Banghua Zhu, Ying Sheng, Lianmin Zheng, Clark W. Barrett, Michael I. Jordan, Jiantao Jiao:
On Optimal Caching and Model Multiplexing for Large Model Inference. CoRR abs/2306.02003 (2023) - [i309]Banghua Zhu, Hiteshi Sharma, Felipe Vieira Frujeri, Shi Dong, Chenguang Zhu, Michael I. Jordan, Jiantao Jiao:
Fine-Tuning Language Models with Advantage-Induced Policy Alignment. CoRR abs/2306.02231 (2023) - [i291]Baihe Huang, Banghua Zhu, Hanlin Zhu, Jason D. Lee, Jiantao Jiao, Michael I. Jordan:
Towards Optimal Statistical Watermarking. CoRR abs/2312.07930 (2023) - 2022
- [c357]Banghua Zhu, Jiantao Jiao, Michael I. Jordan:
Robust Estimation for Non-parametric Families via Generative Adversarial Networks. ISIT 2022: 1100-1105 - [i286]Banghua Zhu, Jiantao Jiao, Michael I. Jordan:
Robust Estimation for Nonparametric Families via Generative Adversarial Networks. CoRR abs/2202.01269 (2022) - [i269]Banghua Zhu, Lun Wang, Qi Pang, Shuai Wang, Jiantao Jiao, Dawn Song, Michael I. Jordan:
Byzantine-Robust Federated Learning with Optimal Statistical Rates and Privacy Guarantees. CoRR abs/2205.11765 (2022) - [i242]Banghua Zhu, Stephen Bates, Zhuoran Yang, Yixin Wang, Jiantao Jiao, Michael I. Jordan:
The Sample Complexity of Online Contract Design. CoRR abs/2211.05732 (2022) - 2019
- [c273]Hongyang Zhang, Yaodong Yu, Jiantao Jiao, Eric P. Xing, Laurent El Ghaoui, Michael I. Jordan:
Theoretically Principled Trade-off between Robustness and Accuracy. ICML 2019: 7472-7482 - [i157]Hongyang Zhang, Yaodong Yu, Jiantao Jiao, Eric P. Xing, Laurent El Ghaoui, Michael I. Jordan:
Theoretically Principled Trade-off between Robustness and Accuracy. CoRR abs/1901.08573 (2019)
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