Követés
Yanjun Han
Yanjun Han
Assistant Professor, New York University
E-mail megerősítve itt: nyu.edu - Kezdőlap
Cím
Hivatkozott rá
Hivatkozott rá
Év
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
2892015
Batched multi-armed bandits problem
Z Gao, Y Han, Z Ren, Z Zhou
Advances in Neural Information Processing Systems 32, 2019
1732019
Performance limits and geometric properties of array localization
Y Han, Y Shen, XP Zhang, MZ Win, H Meng
IEEE Transactions on Information Theory 62 (2), 1054-1075, 2015
1482015
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
1282017
Geometric lower bounds for distributed parameter estimation under communication constraints
Y Han, A Özgür, T Weissman
Conference On Learning Theory, 3163-3188, 2018
1122018
Minimax Estimation of theDistance
J Jiao, Y Han, T Weissman
IEEE Transactions on Information Theory 64 (10), 6672-6706, 2018
1082018
Lower bounds for learning distributions under communication constraints via fisher information
LP Barnes, Y Han, A Ozgur
Journal of Machine Learning Research 21 (236), 1-30, 2020
952020
Optimal rates of entropy estimation over Lipschitz balls
Y Han, J Jiao, T Weissman, Y Wu
892020
Minimax Estimation of Discrete Distributions Under Loss
Y Han, J Jiao, T Weissman
IEEE Transactions on Information Theory 61 (11), 6343-6354, 2015
882015
On the ergodic capacity of MIMO free-space optical systems over turbulence channels
J Zhang, L Dai, Y Han, Y Zhang, Z Wang
IEEE Journal on Selected Areas in Communications 33 (9), 1925-1934, 2015
752015
Demystifying resnet
S Li, J Jiao, Y Han, T Weissman
arXiv preprint arXiv:1611.01186, 2016
702016
Minimax estimation of divergences between discrete distributions
Y Han, J Jiao, T Weissman
IEEE Journal on Selected Areas in Information Theory 1 (3), 814-823, 2020
682020
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
662017
Sequential batch learning in finite-action linear contextual bandits
Y Han, Z Zhou, Z Zhou, J Blanchet, PW Glynn, Y Ye
arXiv preprint arXiv:2004.06321, 2020
572020
Optimal no-regret learning in repeated first-price auctions
Y Han, Z Zhou, T Weissman
arXiv preprint arXiv:2003.09795, 2020
57*2020
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
572018
Distributed statistical estimation of high-dimensional and nonparametric distributions
Y Han, P Mukherjee, A Ozgur, T Weissman
2018 IEEE International Symposium on Information Theory (ISIT), 506-510, 2018
552018
Learning to bid optimally and efficiently in adversarial first-price auctions
Y Han, Z Zhou, A Flores, E Ordentlich, T Weissman
arXiv preprint arXiv:2007.04568, 2020
492020
Local moment matching: A unified methodology for symmetric functional estimation and distribution estimation under wasserstein distance
Y Han, J Jiao, T Weissman
Conference On Learning Theory, 3189-3221, 2018
492018
Tight guarantees for interactive decision making with the decision-estimation coefficient
DJ Foster, N Golowich, Y Han
The Thirty Sixth Annual Conference on Learning Theory, 3969-4043, 2023
412023
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