Banghua Zhu

According to our database, Banghua Zhu authored at least 41 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Noisy Sorting Capacity.

Ziao Wang, Nadim Ghaddar, Banghua Zhu, Lele Wang

IEEE Trans. Inf. Theory, September, 2024

Noisy Computing of the OR and MAX Functions.

Banghua Zhu, Ziao Wang, Nadim Ghaddar, Jiantao Jiao, Lele Wang

IEEE J. Sel. Areas Inf. Theory, 2024

From Crowdsourced Data to High-Quality Benchmarks: Arena-Hard and BenchBuilder Pipeline.

Tianle Li, Wei-Lin Chiang, Evan Frick, Lisa Dunlap, Tianhao Wu, Banghua Zhu, Joseph E. Gonzalez, Ion Stoica

CoRR, 2024

Noisy Computing of the Threshold Function.

Ziao Wang, Nadim Ghaddar, Banghua Zhu, Lele Wang

CoRR, 2024

Generative AI Security: Challenges and Countermeasures.

Banghua Zhu, Norman Mu, Jiantao Jiao, David A. Wagner

CoRR, 2024

Efficient Prompt Caching via Embedding Similarity.

Hanlin Zhu, Banghua Zhu, Jiantao Jiao

CoRR, 2024

Fairness in Serving Large Language Models.

Ying Sheng, Shiyi Cao, Dacheng Li, Banghua Zhu, Zhuohan Li, Danyang Zhuo, Joseph E. Gonzalez, Ion Stoica

Proceedings of the 18th USENIX Symposium on Operating Systems Design and Implementation, 2024

SLoRA: Scalable Serving of Thousands of LoRA Adapters.

Ying Sheng, Shiyi Cao, Dacheng Li, Coleman Hooper, Nicholas Lee, Shuo Yang, Christopher Chou, Banghua Zhu, Lianmin Zheng, Kurt Keutzer, Joseph Gonzalez, Ion Stoica

Proceedings of the Seventh Annual Conference on Machine Learning and Systems, 2024

Guided Online Distillation: Promoting Safe Reinforcement Learning by Offline Demonstration.

Jinning Li, Xinyi Liu, Banghua Zhu, Jiantao Jiao, Masayoshi Tomizuka, Chen Tang, Wei Zhan

Proceedings of the IEEE International Conference on Robotics and Automation, 2024

Iterative Data Smoothing: Mitigating Reward Overfitting and Overoptimization in RLHF.

Banghua Zhu, Michael I. Jordan, Jiantao Jiao

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Chatbot Arena: An Open Platform for Evaluating LLMs by Human Preference.

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

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Towards the Fundamental Limits of Knowledge Transfer over Finite Domains.

Qingyue Zhao, Banghua Zhu

Proceedings of the Twelfth International Conference on Learning Representations, 2024

The Effective Horizon Explains Deep RL Performance in Stochastic Environments.

Cassidy Laidlaw, Banghua Zhu, Stuart Russell, Anca D. Dragan

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Towards Optimal Statistical Watermarking.

Baihe Huang, Banghua Zhu, Hanlin Zhu, Jason D. Lee, Jiantao Jiao, Michael I. Jordan

CoRR, 2023

S-LoRA: Serving Thousands of Concurrent LoRA Adapters.

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

CoRR, 2023

QFT: Quantized Full-parameter Tuning of LLMs with Affordable Resources.

Zhikai Li, Xiaoxuan Liu, Banghua Zhu, Zhen Dong, Qingyi Gu, Kurt Keutzer

CoRR, 2023

Pairwise Proximal Policy Optimization: Harnessing Relative Feedback for LLM Alignment.

Tianhao Wu, Banghua Zhu, Ruoyu Zhang, Zhaojin Wen, Kannan Ramchandran, Jiantao Jiao

CoRR, 2023

Fine-Tuning Language Models with Advantage-Induced Policy Alignment.

Banghua Zhu, Hiteshi Sharma, Felipe Vieira Frujeri, Shi Dong, Chenguang Zhu, Michael I. Jordan, Jiantao Jiao

CoRR, 2023

On Optimal Caching and Model Multiplexing for Large Model Inference.

Banghua Zhu, Ying Sheng, Lianmin Zheng, Clark W. Barrett, Michael I. Jordan, Jiantao Jiao

CoRR, 2023

Online Learning in a Creator Economy.

Banghua Zhu, Sai Praneeth Karimireddy, Jiantao Jiao, Michael I. Jordan

CoRR, 2023

The Sample Complexity of Online Contract Design.

Banghua Zhu, Stephen Bates, Zhuoran Yang, Yixin Wang, Jiantao Jiao, Michael I. Jordan

Proceedings of the 24th ACM Conference on Economics and Computation, 2023

Doubly-Robust Self-Training.

Banghua Zhu, Mingyu Ding, Philip L. Jacobson, Ming Wu, Wei Zhan, Michael I. Jordan, Jiantao Jiao

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Towards Optimal Caching and Model Selection for Large Model Inference.

Banghua Zhu, Ying Sheng, Lianmin Zheng, Clark W. Barrett, Michael I. Jordan, Jiantao Jiao

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

On the Optimal Bounds for Noisy Computing.

Banghua Zhu, Ziao Wang, Nadim Ghaddar, Jiantao Jiao, Lele Wang

Proceedings of the IEEE International Symposium on Information Theory, 2023

Variable-Length Insertion-Based Noisy Sorting.

Ziao Wang, Nadim Ghaddar, Banghua Zhu, Lele Wang

Proceedings of the IEEE International Symposium on Information Theory, 2023

Principled Reinforcement Learning with Human Feedback from Pairwise or K-wise Comparisons.

Banghua Zhu, Michael I. Jordan, Jiantao Jiao

Proceedings of the International Conference on Machine Learning, 2023

Online Learning in Stackelberg Games with an Omniscient Follower.

Geng Zhao, Banghua Zhu, Jiantao Jiao, Michael I. Jordan

Proceedings of the International Conference on Machine Learning, 2023

Jump-Start Reinforcement Learning.

Ikechukwu Uchendu, Ted Xiao, Yao Lu, Banghua Zhu, Mengyuan Yan, Joséphine Simon, Matthew Bennice, Chuyuan Fu, Cong Ma, Jiantao Jiao, Sergey Levine, Karol Hausman

Proceedings of the International Conference on Machine Learning, 2023

Byzantine-Robust Federated Learning with Optimal Statistical Rates.

Banghua Zhu, Lun Wang, Qi Pang, Shuai Wang, Jiantao Jiao, Dawn Song, Michael I. Jordan

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Bridging Offline Reinforcement Learning and Imitation Learning: A Tale of Pessimism.

Paria Rashidinejad, Banghua Zhu, Cong Ma, Jiantao Jiao, Stuart Russell

IEEE Trans. Inf. Theory, 2022

Minimax Off-Policy Evaluation for Multi-Armed Bandits.

Cong Ma, Banghua Zhu, Jiantao Jiao, Martin J. Wainwright

IEEE Trans. Inf. Theory, 2022

Byzantine-Robust Federated Learning with Optimal Statistical Rates and Privacy Guarantees.

Banghua Zhu, Lun Wang, Qi Pang, Shuai Wang, Jiantao Jiao, Dawn Song, Michael I. Jordan

CoRR, 2022

Robust Estimation for Nonparametric Families via Generative Adversarial Networks.

Banghua Zhu, Jiantao Jiao, Michael I. Jordan

CoRR, 2022

Robust Estimation for Non-parametric Families via Generative Adversarial Networks.

Banghua Zhu, Jiantao Jiao, Michael I. Jordan

Proceedings of the IEEE International Symposium on Information Theory, 2022

2021

Linear Representation Meta-Reinforcement Learning for Instant Adaptation.

Matt Peng, Banghua Zhu, Jiantao Jiao

CoRR, 2021

2020

Deconstructing Generative Adversarial Networks.

Banghua Zhu, Jiantao Jiao, David Tse

IEEE Trans. Inf. Theory, 2020

Robust estimation via generalized quasi-gradients.

Banghua Zhu, Jiantao Jiao, Jacob Steinhardt

CoRR, 2020

When does the Tukey Median work?

Banghua Zhu, Jiantao Jiao, Jacob Steinhardt

Proceedings of the IEEE International Symposium on Information Theory, 2020

2019

Joint Transceiver Optimization for Wireless Communication PHY Using Neural Network.

Banghua Zhu, Jintao Wang, Longzhuang He, Jian Song

IEEE J. Sel. Areas Commun., 2019

Generalized Resilience and Robust Statistics.

Banghua Zhu, Jiantao Jiao, Jacob Steinhardt

CoRR, 2019

2017

Sparse Tensor Decomposition for Haplotype Assembly of Diploids and Polyploids.

Abolfazl Hashemi, Banghua Zhu, Haris Vikalo

Proceedings of the 8th ACM International Conference on Bioinformatics, 2017