Jiantao Jiao

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Tsachy WeissmanProfessor of Electrical Engineering at Stanford UniversityVerified email at stanford.edu
Banghua ZhuUniversity of California, BerkeleyVerified email at berkeley.edu
Yanjun HanAssistant Professor, New York UniversityVerified email at nyu.edu
Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC BerkeleyVerified email at cs.berkeley.edu
Kartik VenkatGraduate Student, Stanford UniversityVerified email at alumni.stanford.edu
Eric XingPresident at Mohamed bin Zayed University of AI, Professor of Computer Science, Carnegie Mellon UVerified email at cs.cmu.edu
Hongyang ZhangAssistant Professor of Computer Science, University of WaterlooVerified email at uwaterloo.ca
Paria RashidinejadPostdoctoral Scholar, University of California, BerkeleyVerified email at berkeley.edu
Stuart RussellProfessor of Computer Science, University of California, BerkeleyVerified email at cs.berkeley.edu
Kannan RamchandranProfessor of Electrical Engineering and Computer Science, UC BerkeleyVerified email at eecs.berkeley.edu
Cong MaUniversity of ChicagoVerified email at uchicago.edu
Hanlin ZhuPh.D. student, University of California, BerkeleyVerified email at berkeley.edu
Yaodong YuUniversity of California, BerkeleyVerified email at berkeley.edu
Laurent El GhaouiUC Berkeley (EECS, IEOR)Verified email at berkeley.edu
Nived RajaramanEECS PhD student at UC BerkeleyVerified email at berkeley.edu
Thomas CourtadeAssociate Professor, UC BerkeleyVerified email at berkeley.edu
Tianhao WuUniversity of California, BerkeleyVerified email at berkeley.edu
Jacob SteinhardtStanford UniversityVerified email at cs.stanford.edu
Haim H. PermuterBen Gurion UniversityVerified email at bgu.ac.il
Young-Han KimUniversity of California, San DiegoVerified email at ucsd.edu

Jiantao Jiao

Assistant Professor of EECS and Statistics, University of California, Berkeley

Verified email at berkeley.edu - Homepage

Generative AI Large Language Models Reinforcement Learning Machine Learning AI security


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Theoretically principled trade-off between robustness and accuracy H Zhang, Y Yu, J Jiao, EP Xing, LE Ghaoui, MI Jordan Proceedings of the 36th International Conference on Machine Learning, Long …, 2019	2641	2019
Bridging offline reinforcement learning and imitation learning: A tale of pessimism P Rashidinejad, B Zhu, C Ma, J Jiao, S Russell Advances in Neural Information Processing Systems 34, 11702-11716, 2021	301	2021
Minimax estimation of functionals of discrete distributions J Jiao, K Venkat, Y Han, T Weissman IEEE Transactions on Information Theory 61 (5), 2835-2885, 2015	280	2015
Universal Estimation of Directed Information J Jiao, HH Permuter, L Zhao, YH Kim, T Weissman Information Theory, IEEE Transactions on 59 (10), 6220-6242, 2013	172	2013
Maximum Likelihood Estimation of Functionals of Discrete Distributions J Jiao, K Venkat, Y Han, T Weissman IEEE Transactions on Information Theory 63 (10), 6774 - 6798, 2017	139*	2017
Principled reinforcement learning with human feedback from pairwise or k-wise comparisons B Zhu, M Jordan, J Jiao International Conference on Machine Learning, 43037-43067, 2023	129	2023
Minimax Estimation of theDistance J Jiao, Y Han, T Weissman IEEE Transactions on Information Theory 64 (10), 6672-6706, 2018	104	2018
Minimax Estimation of Discrete Distributions Under Loss Y Han, J Jiao, T Weissman IEEE Transactions on Information Theory 61 (11), 6343-6354, 2015	104*	2015
Jump-start reinforcement learning I Uchendu, T Xiao, Y Lu, B Zhu, M Yan, J Simon, M Bennice, C Fu, C Ma, ... International Conference on Machine Learning, 34556-34583, 2023	94	2023
Optimal rates of entropy estimation over Lipschitz balls Y Han, J Jiao, T Weissman, Y Wu Annals of Statistics, 2017	87	2017
Toward the fundamental limits of imitation learning N Rajaraman, L Yang, J Jiao, K Ramchandran Advances in Neural Information Processing Systems 33, 2914-2924, 2020	73	2020
Securing secure aggregation: Mitigating multi-round privacy leakage in federated learning J So, RE Ali, B Güler, J Jiao, AS Avestimehr Proceedings of the AAAI Conference on Artificial Intelligence 37 (8), 9864-9873, 2023	70	2023
Minimax Estimation of Divergences between Discrete Distributions Y Han, J Jiao, T Weissman IEEE Journal on Selected Areas in Information Theory,, 2020	70	2020
Justification of logarithmic loss via the benefit of side information J Jiao, TA Courtade, K Venkat, T Weissman IEEE Transactions on Information Theory 61 (10), 5357-5365, 2015	67	2015
Dependence measures bounding the exploration bias for general measurements J Jiao, Y Han, T Weissman 2017 IEEE International Symposium on Information Theory (ISIT), 1475-1479, 2017	61	2017
The nearest neighbor information estimator is adaptively near minimax rate-optimal J Jiao, W Gao, Y Han Advances in neural information processing systems 31, 2018	56	2018
Starling-7b: Improving llm helpfulness & harmlessness with rlaif B Zhu, E Frick, T Wu, H Zhu, J Jiao November, 2023	54	2023
Concentration inequalities for the empirical distribution of discrete distributions: beyond the method of types J Mardia, J Jiao, E Tánczos, RD Nowak, T Weissman Information and Inference: A Journal of the IMA 9 (4), 813-850, 2020	54*	2020
Generalized resilience and robust statistics B Zhu, J Jiao, J Steinhardt The Annals of Statistics 50 (4), 2256-2283, 2022	53	2022
Approximate profile maximum likelihood DS Pavlichin, J Jiao, T Weissman Journal of Machine Learning Research 20 (122), 1-55, 2019	51	2019

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