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Banghua Zhu
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2020 – today
- 2024
- [j6]Banghua Zhu
, Ziao Wang
Noisy Computing of the OR and MAX Functions. IEEE J. Sel. Areas Inf. Theory 5: 302-313 (2024) - [j5]Ziao Wang
Noisy Sorting Capacity. IEEE Trans. Inf. Theory 70(9): 6121-6138 (2024) - [c20]Cassidy Laidlaw, Banghua Zhu, Stuart Russell, Anca D. Dragan:
The Effective Horizon Explains Deep RL Performance in Stochastic Environments. ICLR 2024 - [c19]Qingyue Zhao, Banghua Zhu:
Towards the Fundamental Limits of Knowledge Transfer over Finite Domains. ICLR 2024 - [c18]Wei-Lin Chiang, Lianmin Zheng, Ying Sheng, Anastasios Nikolas Angelopoulos, Tianle Li, Dacheng Li, Banghua Zhu, Hao Zhang, Michael I. Jordan, Joseph E. Gonzalez, Ion Stoica:
Chatbot Arena: An Open Platform for Evaluating LLMs by Human Preference. ICML 2024 - [c17]Banghua Zhu, Michael I. Jordan, Jiantao Jiao:
Iterative Data Smoothing: Mitigating Reward Overfitting and Overoptimization in RLHF. ICML 2024 - [c16]Jinning Li, Xinyi Liu, Banghua Zhu, Jiantao Jiao, Masayoshi Tomizuka, Chen Tang, Wei Zhan:
Guided Online Distillation: Promoting Safe Reinforcement Learning by Offline Demonstration. ICRA 2024: 7447-7454 - [c15]Ying Sheng, Shiyi Cao, Dacheng Li, Coleman Hooper, Nicholas Lee, Shuo Yang, Christopher Chou, Banghua Zhu, Lianmin Zheng, Kurt Keutzer, Joseph Gonzalez, Ion Stoica:
SLoRA: Scalable Serving of Thousands of LoRA Adapters. MLSys 2024 - [c14]Ying Sheng, Shiyi Cao, Dacheng Li, Banghua Zhu, Zhuohan Li, Danyang Zhuo, Joseph E. Gonzalez, Ion Stoica:
Fairness in Serving Large Language Models. OSDI 2024: 965-988 - [i34]Ying Sheng, Shiyi Cao, Dacheng Li, Banghua Zhu, Zhuohan Li, Danyang Zhuo, Joseph E. Gonzalez, Ion Stoica:
Fairness in Serving Large Language Models. CoRR abs/2401.00588 (2024) - [i33]Banghua Zhu, Michael I. Jordan, Jiantao Jiao:
Iterative Data Smoothing: Mitigating Reward Overfitting and Overoptimization in RLHF. CoRR abs/2401.16335 (2024) - [i32]Hanlin Zhu, Banghua Zhu, Jiantao Jiao:
Efficient Prompt Caching via Embedding Similarity. CoRR abs/2402.01173 (2024) - [i31]Banghua Zhu, Norman Mu, Jiantao Jiao, David A. Wagner:
Generative AI Security: Challenges and Countermeasures. CoRR abs/2402.12617 (2024) - [i30]Wei-Lin Chiang, Lianmin Zheng, Ying Sheng, Anastasios Nikolas Angelopoulos, Tianle Li, Dacheng Li, Hao Zhang, Banghua Zhu, Michael I. Jordan, Joseph E. Gonzalez, Ion Stoica:
Chatbot Arena: An Open Platform for Evaluating LLMs by Human Preference. CoRR abs/2403.04132 (2024) - [i29]Ziao Wang, Nadim Ghaddar, Banghua Zhu, Lele Wang:
Noisy Computing of the Threshold Function. CoRR abs/2403.07227 (2024) - [i28]Tianle Li, Wei-Lin Chiang, Evan Frick, Lisa Dunlap, Tianhao Wu, Banghua Zhu, Joseph E. Gonzalez, Ion Stoica:
From Crowdsourced Data to High-Quality Benchmarks: Arena-Hard and BenchBuilder Pipeline. CoRR abs/2406.11939 (2024) - [i27]Jixuan Leng, Chengsong Huang, Banghua Zhu, Jiaxin Huang:
Taming Overconfidence in LLMs: Reward Calibration in RLHF. CoRR abs/2410.09724 (2024) - 2023
- [c13]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 - [c12]Ikechukwu Uchendu, Ted Xiao, Yao Lu, Banghua Zhu, Mengyuan Yan, Joséphine Simon, Matthew Bennice, Chuyuan Fu, Cong Ma, Jiantao Jiao, Sergey Levine, Karol Hausman:
Jump-Start Reinforcement Learning. ICML 2023: 34556-34583 - [c11]Geng Zhao, Banghua Zhu, Jiantao Jiao, Michael I. Jordan:
Online Learning in Stackelberg Games with an Omniscient Follower. ICML 2023: 42304-42316 - [c10]Banghua Zhu, Michael I. Jordan, Jiantao Jiao:
Principled Reinforcement Learning with Human Feedback from Pairwise or K-wise Comparisons. ICML 2023: 43037-43067 - [c9]Ziao Wang, Nadim Ghaddar, Banghua Zhu, Lele Wang:
Variable-Length Insertion-Based Noisy Sorting. ISIT 2023: 1782-1787 - [c8]Banghua Zhu, Ziao Wang, Nadim Ghaddar, Jiantao Jiao, Lele Wang:
On the Optimal Bounds for Noisy Computing. ISIT 2023: 1788-1793 - [c7]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 - [c6]Banghua Zhu, Mingyu Ding, Philip L. Jacobson, Ming Wu, Wei Zhan, Michael I. Jordan, Jiantao Jiao:
Doubly-Robust Self-Training. NeurIPS 2023 - [c5]Banghua Zhu
The Sample Complexity of Online Contract Design. EC 2023: 1188 - [i26]Banghua Zhu, Jiantao Jiao, Michael I. Jordan:
Principled Reinforcement Learning with Human Feedback from Pairwise or K-wise Comparisons. CoRR abs/2301.11270 (2023) - [i25]Geng Zhao, Banghua Zhu, Jiantao Jiao, Michael I. Jordan:
Online Learning in Stackelberg Games with an Omniscient Follower. CoRR abs/2301.11518 (2023) - [i24]Banghua Zhu, Sai Praneeth Karimireddy, Jiantao Jiao, Michael I. Jordan:
Online Learning in a Creator Economy. CoRR abs/2305.11381 (2023) - [i23]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) - [i22]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) - [i21]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) - [i20]Banghua Zhu, Ziao Wang, Nadim Ghaddar, Jiantao Jiao, Lele Wang:
On the Optimal Bounds for Noisy Computing. CoRR abs/2306.11951 (2023) - [i19]Banghua Zhu, Ziao Wang, Nadim Ghaddar, Jiantao Jiao, Lele Wang:
Noisy Computing of the OR and MAX Functions. CoRR abs/2309.03986 (2023) - [i18]Jinning Li, Xinyi Liu, Banghua Zhu, Jiantao Jiao, Masayoshi Tomizuka, Chen Tang, Wei Zhan:
Guided Online Distillation: Promoting Safe Reinforcement Learning by Offline Demonstration. CoRR abs/2309.09408 (2023) - [i17]Tianhao Wu, Banghua Zhu, Ruoyu Zhang, Zhaojin Wen, Kannan Ramchandran, Jiantao Jiao:
Pairwise Proximal Policy Optimization: Harnessing Relative Feedback for LLM Alignment. CoRR abs/2310.00212 (2023) - [i16]Zhikai Li, Xiaoxuan Liu, Banghua Zhu, Zhen Dong, Qingyi Gu, Kurt Keutzer:
QFT: Quantized Full-parameter Tuning of LLMs with Affordable Resources. CoRR abs/2310.07147 (2023) - [i15]Qingyue Zhao, Banghua Zhu:
Towards the Fundamental Limits of Knowledge Transfer over Finite Domains. CoRR abs/2310.07838 (2023) - [i14]Ying Sheng, Shiyi Cao, Dacheng Li, Coleman Hooper, Nicholas Lee, Shuo Yang, Christopher Chou, Banghua Zhu, Lianmin Zheng, Kurt Keutzer, Joseph E. Gonzalez, Ion Stoica:
S-LoRA: Serving Thousands of Concurrent LoRA Adapters. CoRR abs/2311.03285 (2023) - [i13]Baihe Huang, Banghua Zhu, Hanlin Zhu, Jason D. Lee, Jiantao Jiao, Michael I. Jordan:
Towards Optimal Statistical Watermarking. CoRR abs/2312.07930 (2023) - [i12]Cassidy Laidlaw, Banghua Zhu, Stuart Russell, Anca D. Dragan:
The Effective Horizon Explains Deep RL Performance in Stochastic Environments. CoRR abs/2312.08369 (2023) - 2022
- [j4]Cong Ma
Minimax Off-Policy Evaluation for Multi-Armed Bandits. IEEE Trans. Inf. Theory 68(8): 5314-5339 (2022) - [j3]Paria Rashidinejad, Banghua Zhu
Bridging Offline Reinforcement Learning and Imitation Learning: A Tale of Pessimism. IEEE Trans. Inf. Theory 68(12): 8156-8196 (2022) - [c4]Banghua Zhu, Jiantao Jiao, Michael I. Jordan:
Robust Estimation for Non-parametric Families via Generative Adversarial Networks. ISIT 2022: 1100-1105 - [i11]Banghua Zhu, Jiantao Jiao, Michael I. Jordan:
Robust Estimation for Nonparametric Families via Generative Adversarial Networks. CoRR abs/2202.01269 (2022) - [i10]Ikechukwu Uchendu, Ted Xiao, Yao Lu, Banghua Zhu, Mengyuan Yan, Joséphine Simon, Matthew Bennice, Chuyuan Fu, Cong Ma, Jiantao Jiao, Sergey Levine, Karol Hausman:
Jump-Start Reinforcement Learning. CoRR abs/2204.02372 (2022) - [i9]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) - [i8]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) - 2021
- [c3]Paria Rashidinejad, Banghua Zhu, Cong Ma, Jiantao Jiao, Stuart Russell:
Bridging Offline Reinforcement Learning and Imitation Learning: A Tale of Pessimism. NeurIPS 2021: 11702-11716 - [i7]Matt Peng, Banghua Zhu, Jiantao Jiao:
Linear Representation Meta-Reinforcement Learning for Instant Adaptation. CoRR abs/2101.04750 (2021) - [i6]Cong Ma, Banghua Zhu, Jiantao Jiao, Martin J. Wainwright:
Minimax Off-Policy Evaluation for Multi-Armed Bandits. CoRR abs/2101.07781 (2021) - [i5]Paria Rashidinejad, Banghua Zhu, Cong Ma, Jiantao Jiao, Stuart Russell:
Bridging Offline Reinforcement Learning and Imitation Learning: A Tale of Pessimism. CoRR abs/2103.12021 (2021) - 2020
- [j2]Banghua Zhu
Deconstructing Generative Adversarial Networks. IEEE Trans. Inf. Theory 66(11): 7155-7179 (2020) - [c2]Banghua Zhu, Jiantao Jiao, Jacob Steinhardt:
When does the Tukey Median work? ISIT 2020: 1201-1206 - [i4]Banghua Zhu, Jiantao Jiao, Jacob Steinhardt:
When does the Tukey median work? CoRR abs/2001.07805 (2020) - [i3]Banghua Zhu, Jiantao Jiao, Jacob Steinhardt:
Robust estimation via generalized quasi-gradients. CoRR abs/2005.14073 (2020)
2010 – 2019
- 2019
- [j1]Banghua Zhu
Joint Transceiver Optimization for Wireless Communication PHY Using Neural Network. IEEE J. Sel. Areas Commun. 37(6): 1364-1373 (2019) - [i2]Banghua Zhu, Jiantao Jiao, David Tse:
Deconstructing Generative Adversarial Networks. CoRR abs/1901.09465 (2019) - [i1]Banghua Zhu, Jiantao Jiao, Jacob Steinhardt:
Generalized Resilience and Robust Statistics. CoRR abs/1909.08755 (2019) - 2017
- [c1]Abolfazl Hashemi, Banghua Zhu, Haris Vikalo
Sparse Tensor Decomposition for Haplotype Assembly of Diploids and Polyploids. BCB 2017: 764-765
Coauthor Index
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last updated on 2024-11-25 23:43 CET by the dblp team
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