Publications
2023
Optimal No-regret Learning in Repeated First-price Auctions
with Zhengyuan Zhou and Tsachy Weissman
Operations Research, to appear. (slides) (video)
Online Learning in Multi-unit Auctions
with Simina Brânzei, Mahsa Derakhshan, and Negin Golrezaei
NeurIPS, Dec. 2023.
Covariance alignment: from maximum likelihood estimation to Gromov--Wasserstein
with Philippe Rigollet and George Stepaniants
Preprint, Nov. 2023.
Minimax Optimal Testing by Classification
with Patrik R. Gerber and Yury Polyanskiy
COLT, Jul. 2023.
Tight Guarantees for Interactive Decision Making with the Decision-Estimation Coefficient
with Dylan J. Foster and Noah Golowich
COLT, Jul. 2023.
Optimal prediction of Markov chains with and without spectral gap
with Soham Jana and Yihong Wu
IEEE Transactions on Information Theory, Jun. 2023. (NeurIPS’21)
Leveraging Product Variations for Personalized Dynamic Pricing
with Srikanth Jagabathula and Zhengyuan Zhou
Submitted, May 2023.
Statistical Complexity and Optimal Algorithms for Non-linear Ridge Bandits
with Nived Rajaraman, Jiantao Jiao, and Kannan Ramchandran
Preprint, Feb 2023. (slides)
2022
On the amortized complexity of approximate counting
with Ishaq Aden-Ali, Jelani Nelson, and Huacheng Yu
Preprint, Nov 2022.
Leveraging the Hints: Adaptive Bidding in Repeated First-Price Auctions
with Wei Zhang, Zhengyuan Zhou, Aaron Flores, and Tsachy Weissman
NeurIPS, Nov 2022 (Spotlight).
Beyond the Best: Estimating Distribution Functionals in Infinite-Armed Bandits
with Yifei Wang, Tavor Baharav, Jiantao Jiao, and David Tse
NeurIPS, Nov 2022.
Oracle-Efficient Online Learning for Beyond Worst-Case Adversaries
with Nika Haghtalab, Abhishek Shetty, and Kunhe Yang
NeurIPS, Nov 2022 (Designated as Oral).
On the Statistical Complexity of Sample Amplification
with Brian Axelrod, Shivam Garg, Vatsal Sharan, and Gregory Valiant
Preprint, Jan 2022.
2021
On the Value of Interaction and Function Approximation in Imitation Learning
with Nived Rajaraman, Lin F. Yang, Jingbo Liu, Jiantao Jiao, and Kannan Ramchandran
NeurIPS, Dec 2021.
Optimal Communication Rates and Combinatorial Properties for Common Randomness Generation
with Kedar Tatwawadi, Zhengqing Zhou, Gowtham Kurri, Vinod Prabhakaran, and Tsachy Weissman
IEEE Transactions on Information Theory, Dec 2021. (ISIT’21) (slides) (video)
Geometric Lower Bounds for Distributed Parameter Estimation under Communication Constraints
with Ayfer Ozgur and Tsachy Weissman
IEEE Transactions on Information Theory, Dec 2021. (COLT’18) (ISIT’18) (COLT slides) (ISIT slides)
(Errata: Earlier versions (including the conference proceeding) of this paper had a mistake in the lower bound argument for blackboard communication protocols, and the journal version fixes it. Also see the errata.)
MEOW: A Space-Efficient Non-Parametric Bid Shading Algorithm
with Wei Zhang, Brendan Kitts, Zhengyuan Zhou, Tingyu Mao, Hao He, Shengjun Pan, Aaron Flores, San Gultekin, and Tsachy Weissman
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), Aug 2021.
Adversarial Combinatorial Bandits with General Non-linear Reward Functions
with Xi Chen and Yining Wang
ICML, Jul 2021. (slides) (poster)
On the High Accuracy Limitation of Adaptive Property Estimation
AISTATS, Apr 2021. (slides) (poster) (video)
Provably Breaking the Quadratic Error Compounding Barrier in Imitation Learning, Optimally
with Nived Rajaraman, Lin F. Yang, Jiantao Jiao, and Kannan Ramchandran
Preprint, Feb 2022.
On the Competitive Analysis and High Accuracy Optimality of Profile Maximum Likelihood
with Kirankumar Shiragur
SODA, Jan 2021. (slides) (video)
2020
Optimal Rates of Entropy Estimation over Lipschitz Balls
with Jiantao Jiao, Tsachy Weissman, and Yihong Wu
The Annals of Statistics, Dec 2020. (AoS Special Invited Session at JSM 2021) (slides)
Minimax Optimal Nonparametric Estimation of Heterogeneous Treatment Effects
with Zijun Gao
NeurIPS, Dec 2020 (Spotlight).
Minimax Estimation of KL Divergence between Discrete Distributions
with Jiantao Jiao and Tsachy Weissman
Journal on Selected Areas in Information Theory, Nov 2020. (an earlier version) (ISITA’16, Student Paper Award) (slides) (code)
Lower Bounds for Learning Distributions under Communication Constraints via Fisher Information
with Leighton Barnes and Ayfer Ozgur
Journal of Machine Learning Research, Oct 2020. (ISIT’19)
Domain Compression and its Application to Randomness-Optimal Distributed Goodness-of-Fit
with Jayadev Acharya, Clement L. Canonne, Ziteng Sun, and Himanshu Tyagi
COLT, Jul 2020. (short slides) (long slides) (video)
Bias Correction with Jackknife, Bootstrap, and Taylor Series
with Jiantao Jiao
IEEE Transactions on Information Theory, Jul 2020.
Learning to Bid Optimally and Efficiently in Adversarial First-price Auctions
with Zhengyuan Zhou, Aaron Flores, Erik Ordentlich, and Tsachy Weissman
Preprint, Jul 2020. (slides) (video)
On Estimation of $L_r$-norms in Gaussian White Noise Models
with Jiantao Jiao and Rajarshi Mukherjee
Probability Theory and Related Fields, Jun 2020. (slides)
Constrained Functional Value under General Convexity Conditions with Applications to Distributed Simulation
ISIT, Jun 2020.
Sequential Batch Learning in Finite-Action Linear Contextual Bandits
with Zhengqing Zhou, Zhengyuan Zhou, Jose Blanchet, Peter Glynn, and Yinyu Ye
Preprint, Apr 2020.
2019
2018
Entropy Rate Estimation for Markov Chains with Large State Space
with Jiantao Jiao, Chuan-Zheng Lee, Tsachy Weissman, Yihong Wu, and Tiancheng Yu
NIPS, Dec 2018 (Spotlight). (slides) (poster)
The Nearest Neighbor Information Estimator is Adaptively Near Minimax Rate-Optimal
with Jiantao Jiao and Weihao Gao
NIPS, Dec 2018 (Spotlight). (slides) (poster)
Minimax Estimation of the Distance
with Jiantao Jiao and Tsachy Weissman
IEEE Transactions on Information Theory, Oct 2018. (ISIT’16, Best Student Paper Finalist)
Local Moment Matching: a Unified Methodology for Symmetric Functional Estimation and Distribution Estimation under Wasserstein Distance
with Jiantao Jiao and Tsachy Weissman
COLT, Jul 2018. (COLT slides) (Long slides)
Generalizations of Maximal Inequalities to Arbitrary Selection Rules
with Jiantao Jiao and Tsachy Weissman
Statistics & Probability Letters, Jan 2018. (ISIT’17)
2014 - 2017
Maximum Likelihood Estimation of Functionals of Discrete Distributions
with Jiantao Jiao, Kartik Venkat, and Tsachy Weissman
IEEE Transactions on Information Theory, Oct 2017. (ISIT’15a) (ISIT’15b)
Mutual Information Bounds via Adjacency Events
with Or Ordentlich and Ofer Shayevitz
IEEE Transactions on Information Theory, Nov 2016.
Performance Limits and Geometric Properties of Array Localization
with Yuan Shen, Xiao-Ping Zhang, Moe Z. Win, and Huadong Meng
IEEE Transactions on Information Theory, Feb 2016. (ICASSP’14)
Minimax Estimation of Discrete Distributions under $ell_1$ Loss
with Jiantao Jiao and Tsachy Weissman
IEEE Transactions on Information Theory, Nov 2015. (ISIT’15)
On the Ergodic Capacity of MIMO Free-Space Optical Systems over Turbulence Channels
with Jiayi Zhang, Linglong Dai, Yu Zhang, and Zhaocheng Wang
IEEE Journal on Selected Areas in Communications, Sept 2015.
Minimax Estimation of Functionals of Discrete Distributions
with Jiantao Jiao, Kartik Venkat, and Tsachy Weissman
IEEE Transactions on Information Theory, May 2015. (ISIT’15) (code)
Adaptive Estimation of Shannon Entropy
with Jiantao Jiao and Tsachy Weissman
Technical report, Feb 2015. (ISIT’15) (slides)
Beyond Maximum Likelihood: from Theory to Practice
with Jiantao Jiao, Kartik Venkat, and Tsachy Weissman
Technical report, Sept 2014. (Asilomar’16)
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