Jiantao Jiao
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I am an Assistant Professor in the Department of Electrical Engineering and Computer Sciences and Department of Statistics at University of California, Berkeley. I received the Ph.D. degree from Stanford University in 2018. I am a member of the Berkeley Laboratory of Information and System Sciences (BLISS) and the Berkeley Artificial Intelligence Research (BAIR) Lab. I am broadly interested in statistical machine learning, mathematical data science, optimization, applied probability, information theory, and their applications in science and engineering.
Recently, my research has been focusing on the theory and system of robust learning, (inverse) reinforcement learning, the interplay between economics, statistics, and computation, and distributed (permissionless) systems.
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Recent publications
Provably Breaking the Quadratic Error Compounding Barrier in Imitation Learning, Optimally
Nived Rajaraman, Yanjun Han, Lin F. Yang, Kannan Ramchandran, Jiantao Jiao
Minimax Off-Policy Evaluation for Multi-Armed Bandits
Cong Ma, Banghua Zhu, Jiantao Jiao, Martin J. Wainwright
Toward the Fundamental Limits of Imitation Learning
Nived Rajaraman, Lin F. Yang, Jiantao Jiao, Kannan Ramchandran, NeurIPS 2020
SLIP: Learning to Predict in Unknown Dynamical Systems with Long-Term Memory
Paria Rashidinejad, Jiantao Jiao, Stuart Russell, NeurIPS 2020 (Oral)
Robust Estimation via Generalized Quasi-gradients
Banghua Zhu, Jiantao Jiao, Jacob Steinhardt
Generalized Resilience and Robust Statistics
Banghua Zhu, Jiantao Jiao, Jacob Steinhardt
Minimax Estimation of Divergences between Discrete Distributions
Yanjun Han, Jiantao Jiao, Tsachy Weissman
Optimal Rates of Entropy Estimation over Lipschitz Balls
Yanjun Han, Jiantao Jiao, Tsachy Weissman, Yihong Wu, Annals of Statistics
Theoretically Principled Trade-off between Robustness and Accuracy
Hongyang Zhang, Yaodong Yu, Jiantao Jiao, Eric P. Xing, Laurent El Ghaoui, Michael I. Jordan, ICML, 2019
The Nearest Neighbor Information Estimator is Adaptively Near Minimax Rate-Optimal
Jiantao Jiao, Weihao Gao, Yanjun Han, NeurIPS 2018 (Spotlight)
Entropy Rate Estimation for Markov Chains with Large State Space
Yanjun Han, Jiantao Jiao, Chuan-Zheng Lee, Tsachy Weissman, Yihong Wu, Tiancheng Yu, NeurIPS 2018 (Spotlight)
Contact
University of California, Berkeley
Department of Electrical Engineering and Computer Sciences
257M Cory Hall
Berkeley, CA 94720-1770
Email: jiantao [at] eecs [dot] berkeley [dot] edu
Due to the large volume of emails that I receive, I generally do not respond to unsolicited inquiries about student or postdoc openings, or research advice. Nevertheless, if you have a strong quantitative background and think your interests are compatible with mine, please feel free to contact me.
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