Jiantao Jiao

ORCID

Publication Activity (10 Years)

Years Active: 2010-2024
Publications (10 Years): 108

Top Venues

CoRR

ISIT

IEEE Trans. Inf. Theory

NeurIPS

Publications

Hanlin Zhu, Baihe Huang, Shaolun Zhang, Michael I. Jordan, Jiantao Jiao, Yuandong Tian, Stuart Russell
Towards a Theoretical Understanding of the 'Reversal Curse' via Training Dynamics. CoRR (2024)
Banghua Zhu, Norman Mu, Jiantao Jiao, David A. Wagner
Generative AI Security: Challenges and Countermeasures. CoRR (2024)
Banghua Zhu, Michael I. Jordan, Jiantao Jiao
Iterative Data Smoothing: Mitigating Reward Overfitting and Overoptimization in RLHF. CoRR (2024)
Hanlin Zhu, Banghua Zhu, Jiantao Jiao
Efficient Prompt Caching via Embedding Similarity. CoRR (2024)
Banghua Zhu, Ziao Wang, Nadim Ghaddar, Jiantao Jiao, Lele Wang
Noisy Computing of the OR and MAX Functions. IEEE J. Sel. Areas Inf. Theory 5 (2024)
Zhanhao Hu, Julien Piet, Geng Zhao, Jiantao Jiao, David A. Wagner
Toxicity Detection for Free. CoRR (2024)
Tianhao Wu, Weizhe Yuan, Olga Golovneva, Jing Xu, Yuandong Tian, Jiantao Jiao, Jason Weston, Sainbayar Sukhbaatar
Meta-Rewarding Language Models: Self-Improving Alignment with LLM-as-a-Meta-Judge. CoRR (2024)
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)
Nived Rajaraman, Jiantao Jiao, Kannan Ramchandran
Toward a Theory of Tokenization in LLMs. CoRR (2024)
Henry Pinkard, Leyla A. Kabuli, Eric Markley, Tiffany Chien, Jiantao Jiao, Laura Waller
Universal evaluation and design of imaging systems using information estimation. CoRR (2024)
Banghua Zhu, Ziao Wang, Nadim Ghaddar, Jiantao Jiao, Lele Wang
Noisy Computing of the OR and MAX Functions. CoRR (2023)
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)
Banghua Zhu, Mingyu Ding, Philip L. Jacobson, Ming Wu, Wei Zhan, Michael I. Jordan, Jiantao Jiao
Doubly Robust Self-Training. CoRR (2023)
Hanlin Zhu, Paria Rashidinejad, Jiantao Jiao
Importance Weighted Actor-Critic for Optimal Conservative Offline Reinforcement Learning. NeurIPS (2023)
Jinhyun So, Ramy E. Ali, Basak Güler, Jiantao Jiao, Amir Salman Avestimehr
Securing Secure Aggregation: Mitigating Multi-Round Privacy Leakage in Federated Learning. AAAI (2023)
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 (2023)
Banghua Zhu, Mingyu Ding, Philip L. Jacobson, Ming Wu, Wei Zhan, Michael I. Jordan, Jiantao Jiao
Doubly-Robust Self-Training. NeurIPS (2023)
Geng Zhao, Banghua Zhu, Jiantao Jiao, Michael I. Jordan
Online Learning in Stackelberg Games with an Omniscient Follower. ICML (2023)
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 (2023)
Nived Rajaraman, Yanjun Han, Jiantao Jiao, Kannan Ramchandran
Beyond UCB: Statistical Complexity and Optimal Algorithms for Non-linear Ridge Bandits. CoRR (2023)
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)
Hanlin Zhu, Paria Rashidinejad, Jiantao Jiao
Importance Weighted Actor-Critic for Optimal Conservative Offline Reinforcement Learning. CoRR (2023)
Banghua Zhu, Ziao Wang, Nadim Ghaddar, Jiantao Jiao, Lele Wang
On the Optimal Bounds for Noisy Computing. CoRR (2023)
Tianhao Wu, Banghua Zhu, Ruoyu Zhang, Zhaojin Wen, Kannan Ramchandran, Jiantao Jiao
Pairwise Proximal Policy Optimization: Harnessing Relative Feedback for LLM Alignment. CoRR (2023)
Banghua Zhu, Ziao Wang, Nadim Ghaddar, Jiantao Jiao, Lele Wang
On the Optimal Bounds for Noisy Computing. ISIT (2023)
Banghua Zhu, Stephen Bates, Zhuoran Yang, Yixin Wang, Jiantao Jiao, Michael I. Jordan
The Sample Complexity of Online Contract Design. EC (2023)
Hanlin Zhu, Andrew Cohen, Danqing Wang, Kevin Yang, Xiaomeng Yang, Jiantao Jiao, Yuandong Tian
End-to-end Story Plot Generator. CoRR (2023)
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)
Paria Rashidinejad, Hanlin Zhu, Kunhe Yang, Stuart Russell, Jiantao Jiao
Optimal Conservative Offline RL with General Function Approximation via Augmented Lagrangian. ICLR (2023)
Baihe Huang, Banghua Zhu, Hanlin Zhu, Jason D. Lee, Jiantao Jiao, Michael I. Jordan
Towards Optimal Statistical Watermarking. CoRR (2023)
Banghua Zhu, Jiantao Jiao, Michael I. Jordan
Principled Reinforcement Learning with Human Feedback from Pairwise or K-wise Comparisons. CoRR (2023)
Banghua Zhu, Sai Praneeth Karimireddy, Jiantao Jiao, Michael I. Jordan
Online Learning in a Creator Economy. CoRR (2023)
Banghua Zhu, Michael I. Jordan, Jiantao Jiao
Principled Reinforcement Learning with Human Feedback from Pairwise or K-wise Comparisons. ICML (2023)
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 (2023)
Geng Zhao, Banghua Zhu, Jiantao Jiao, Michael I. Jordan
Online Learning in Stackelberg Games with an Omniscient Follower. CoRR (2023)
Banghua Zhu, Jiantao Jiao, Michael I. Jordan
Robust Estimation for Non-parametric Families via Generative Adversarial Networks. ISIT (2022)
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 (2022)
Yifei Wang, Tavor Z. Baharav, Yanjun Han, Jiantao Jiao, David Tse
Beyond the Best: Estimating Distribution Functionals in Infinite-Armed Bandits. CoRR (2022)
Yuexiang Zhai, Christina Baek, Zhengyuan Zhou, Jiantao Jiao, Yi Ma
Computational Benefits of Intermediate Rewards for Goal-Reaching Policy Learning. J. Artif. Intell. Res. 73 (2022)
Cong Ma, Banghua Zhu, Jiantao Jiao, Martin J. Wainwright
Minimax Off-Policy Evaluation for Multi-Armed Bandits. IEEE Trans. Inf. Theory 68 (8) (2022)
Yifei Wang, Tavor Z. Baharav, Yanjun Han, Jiantao Jiao, David Tse
Beyond the Best: Distribution Functional Estimation in Infinite-Armed Bandits. NeurIPS (2022)
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 (2022)
Banghua Zhu, Stephen Bates, Zhuoran Yang, Yixin Wang, Jiantao Jiao, Michael I. Jordan
The Sample Complexity of Online Contract Design. CoRR (2022)
Banghua Zhu, Jiantao Jiao, Michael I. Jordan
Robust Estimation for Nonparametric Families via Generative Adversarial Networks. CoRR (2022)
Paria Rashidinejad, Hanlin Zhu, Kunhe Yang, Stuart Russell, Jiantao Jiao
Optimal Conservative Offline RL with General Function Approximation via Augmented Lagrangian. CoRR (2022)
Gokul Swamy, Nived Rajaraman, Matthew Peng, Sanjiban Choudhury, J. Andrew Bagnell, Steven Wu, Jiantao Jiao, Kannan Ramchandran
Minimax Optimal Online Imitation Learning via Replay Estimation. NeurIPS (2022)
Tianhao Wu, Yunchang Yang, Han Zhong, Liwei Wang, Simon S. Du, Jiantao Jiao
Nearly Optimal Policy Optimization with Stable at Any Time Guarantee. ICML (2022)
Paria Rashidinejad, Banghua Zhu, Cong Ma, Jiantao Jiao, Stuart Russell
Bridging Offline Reinforcement Learning and Imitation Learning: A Tale of Pessimism. IEEE Trans. Inf. Theory 68 (12) (2022)
Gokul Swamy, Nived Rajaraman, Matthew Peng, Sanjiban Choudhury, J. Andrew Bagnell, Zhiwei Steven Wu, Jiantao Jiao, Kannan Ramchandran
Minimax Optimal Online Imitation Learning via Replay Estimation. CoRR (2022)
Jinhyun So, Ramy E. Ali, Basak Guler, Jiantao Jiao, Salman Avestimehr
Securing Secure Aggregation: Mitigating Multi-Round Privacy Leakage in Federated Learning. IACR Cryptol. ePrint Arch. 2021 (2021)
Nived Rajaraman, Yanjun Han, Lin F. Yang, Kannan Ramchandran, Jiantao Jiao
Provably Breaking the Quadratic Error Compounding Barrier in Imitation Learning, Optimally. CoRR (2021)
Jinhyun So, Ramy E. Ali, Basak Guler, Jiantao Jiao, Salman Avestimehr
Securing Secure Aggregation: Mitigating Multi-Round Privacy Leakage in Federated Learning. CoRR (2021)
Tianjun Zhang, Paria Rashidinejad, Jiantao Jiao, Yuandong Tian, Joseph Gonzalez, Stuart Russell
MADE: Exploration via Maximizing Deviation from Explored Regions. CoRR (2021)
Tianjun Zhang, Paria Rashidinejad, Jiantao Jiao, Yuandong Tian, Joseph E. Gonzalez, Stuart Russell
MADE: Exploration via Maximizing Deviation from Explored Regions. NeurIPS (2021)
Tianhao Wu, Yunchang Yang, Han Zhong, Liwei Wang, Simon S. Du, Jiantao Jiao
Nearly Optimal Policy Optimization with Stable at Any Time Guarantee. CoRR (2021)
Paria Rashidinejad, Banghua Zhu, Cong Ma, Jiantao Jiao, Stuart Russell
Bridging Offline Reinforcement Learning and Imitation Learning: A Tale of Pessimism. NeurIPS (2021)
Yuexiang Zhai, Christina Baek, Zhengyuan Zhou, Jiantao Jiao, Yi Ma
Computational Benefits of Intermediate Rewards for Hierarchical Planning. CoRR (2021)
Paria Rashidinejad, Banghua Zhu, Cong Ma, Jiantao Jiao, Stuart Russell
Bridging Offline Reinforcement Learning and Imitation Learning: A Tale of Pessimism. CoRR (2021)
Matt Peng, Banghua Zhu, Jiantao Jiao
Linear Representation Meta-Reinforcement Learning for Instant Adaptation. CoRR (2021)
Cong Ma, Banghua Zhu, Jiantao Jiao, Martin J. Wainwright
Minimax Off-Policy Evaluation for Multi-Armed Bandits. CoRR (2021)
Nived Rajaraman, Yanjun Han, Lin Yang, Jingbo Liu, Jiantao Jiao, Kannan Ramchandran
On the Value of Interaction and Function Approximation in Imitation Learning. NeurIPS (2021)
Banghua Zhu, Jiantao Jiao, Jacob Steinhardt
When does the Tukey median work? CoRR (2020)
Banghua Zhu, Jiantao Jiao, Jacob Steinhardt
When does the Tukey Median work? ISIT (2020)
Paria Rashidinejad, Jiantao Jiao, Stuart Russell
SLIP: Learning to Predict in Unknown Dynamical Systems with Long-Term Memory. CoRR (2020)
Jiantao Jiao, Yanjun Han
Bias Correction With Jackknife, Bootstrap, and Taylor Series. IEEE Trans. Inf. Theory 66 (7) (2020)
Banghua Zhu, Jiantao Jiao, David Tse
Deconstructing Generative Adversarial Networks. IEEE Trans. Inf. Theory 66 (11) (2020)
Nived Rajaraman, Lin F. Yang, Jiantao Jiao, Kannan Ramchandran
Toward the Fundamental Limits of Imitation Learning. NeurIPS (2020)
Banghua Zhu, Jiantao Jiao, Jacob Steinhardt
Robust estimation via generalized quasi-gradients. CoRR (2020)
Nived Rajaraman, Lin F. Yang, Jiantao Jiao, Kannan Ramchandran
Toward the Fundamental Limits of Imitation Learning. CoRR (2020)
Yanjun Han, Jiantao Jiao, Tsachy Weissman
Minimax Estimation of Divergences Between Discrete Distributions. IEEE J. Sel. Areas Inf. Theory 1 (3) (2020)
Paria Rashidinejad, Jiantao Jiao, Stuart Russell
SLIP: Learning to predict in unknown dynamical systems with long-term memory. NeurIPS (2020)
Banghua Zhu, Jiantao Jiao, Jacob Steinhardt
Generalized Resilience and Robust Statistics. CoRR (2019)
Hongyang Zhang, Yaodong Yu, Jiantao Jiao, Eric P. Xing, Laurent El Ghaoui, Michael I. Jordan
Theoretically Principled Trade-off between Robustness and Accuracy. CoRR (2019)
Giulia C. Fanti, Jiantao Jiao, Ashok Vardhan Makkuva, Sewoong Oh, Ranvir Rana, Pramod Viswanath
Barracuda: The Power of ℓ-polling in Proof-of-Stake Blockchains. MobiHoc (2019)
Jiantao Jiao, Yanjun Han, Irena Fischer-Hwang, Tsachy Weissman
Estimating the Fundamental Limits is Easier Than Achieving the Fundamental Limits. IEEE Trans. Inf. Theory 65 (10) (2019)
Dmitri S. Pavlichin, Jiantao Jiao, Tsachy Weissman
Approximate Profile Maximum Likelihood. J. Mach. Learn. Res. 20 (2019)
Giulia C. Fanti, Jiantao Jiao, Ashok Vardhan Makkuva, Sewoong Oh, Ranvir Rana, Pramod Viswanath
Barracuda: The Power of 𝓁-polling in Proof-of-Stake Blockchains. CoRR (2019)
Banghua Zhu, Jiantao Jiao, David Tse
Deconstructing Generative Adversarial Networks. CoRR (2019)
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)
Jiantao Jiao, Yanjun Han, Tsachy Weissman
Distance. IEEE Trans. Inf. Theory 64 (10) (2018)
Yanjun Han, Jiantao Jiao, Tsachy Weissman
Local moment matching: A unified methodology for symmetric functional estimation and distribution estimation under Wasserstein distance. CoRR (2018)
Jay Mardia, Jiantao Jiao, Ervin Tanczos, Robert D. Nowak, Tsachy Weissman
Concentration Inequalities for the Empirical Distribution. CoRR (2018)
Jiantao Jiao, Kartik Venkat, Tsachy Weissman
Mutual Information, Relative Entropy and Estimation Error in Semi-Martingale Channels. IEEE Trans. Inf. Theory 64 (10) (2018)
Yanjun Han, Jiantao Jiao, Chuan-Zheng Lee, Tsachy Weissman, Yihong Wu, Tiancheng Yu
Entropy Rate Estimation for Markov Chains with Large State Space. CoRR (2018)
Kedar Tatwawadi, Jiantao Jiao, Tsachy Weissman
Minimax Redundancy for Markov Chains with Large State Space. ISIT (2018)
Yanjun Han, Jiantao Jiao, Tsachy Weissman
Local moment matching: A unified methodology for symmetric functional estimation and distribution estimation under Wasserstein distance. COLT (2018)
Jiantao Jiao, Weihao Gao, Yanjun Han
The Nearest Neighbor Information Estimator is Adaptively Near Minimax Rate-Optimal. NeurIPS (2018)
Yanjun Han, Jiantao Jiao, Chuan-Zheng Lee, Tsachy Weissman, Yihong Wu, Tiancheng Yu
Entropy Rate Estimation for Markov Chains with Large State Space. NeurIPS (2018)
Kedar Shriram Tatwawadi, Jiantao Jiao, Tsachy Weissman
Minimax redundancy for Markov chains with large state space. CoRR (2018)
Hongyang Zhang, Susu Xu, Jiantao Jiao, Pengtao Xie, Ruslan Salakhutdinov, Eric P. Xing
Stackelberg GAN: Towards Provable Minimax Equilibrium via Multi-Generator Architectures. CoRR (2018)
Jiantao Jiao, Weihao Gao, Yanjun Han
The Nearest Neighbor Information Estimator is Adaptively Near Minimax Rate-Optimal. CoRR (2017)
Jiantao Jiao, Yanjun Han, Tsachy Weissman
Dependence measures bounding the exploration bias for general measurements. ISIT (2017)
Jiantao Jiao, Kartik Venkat, Yanjun Han, Tsachy Weissman
Maximum Likelihood Estimation of Functionals of Discrete Distributions. IEEE Trans. Inf. Theory 63 (10) (2017)
Yanjun Han, Jiantao Jiao, Tsachy Weissman, Yihong Wu
Optimal rates of entropy estimation over Lipschitz balls. CoRR (2017)
Dmitri S. Pavlichin, Jiantao Jiao, Tsachy Weissman
Approximate Profile Maximum Likelihood. CoRR (2017)
Jiantao Jiao, Kartik Venkat, Tsachy Weissman
Mutual Information, Relative Entropy and Estimation Error in Semi-martingale Channels. CoRR (2017)
Jiantao Jiao, Yanjun Han, Irena Fischer-Hwang, Tsachy Weissman
Estimating the Fundamental Limits is Easier than Achieving the Fundamental Limits. CoRR (2017)
Yanjun Han, Jiantao Jiao, Rajarshi Mukherjee, Tsachy Weissman
-Norms in Gaussian White Noise Models. CoRR (2017)
Jiantao Jiao, Yanjun Han, Tsachy Weissman
Bias Correction with Jackknife, Bootstrap, and Taylor Series. CoRR (2017)
Jiantao Jiao, Yanjun Han, Tsachy Weissman
Minimax Estimation of the $L_1$ Distance. CoRR (2017)

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Publication Activity (10 Years)

Top Topics

Top Venues

Jiantao Jiao