Nian Si

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Jose BlanchetStanford UniversityVerified email at stanford.edu
Zhengyuan ZhouDept of Technology, Operations and Statistics at NYU SternVerified email at stern.nyu.edu
Shengbo WangPh.D. candidate, Stanford UniversityVerified email at stanford.edu
Fan ZhangManagement Science and Engineering, Stanford UniversityVerified email at stanford.edu
Karthyek MurthySingapore University of Technology and DesignVerified email at sutd.edu.sg
Viet Anh NguyenThe Chinese University of Hong KongVerified email at cuhk.edu.hk
J. Michael HarrisonProfessor of Management, Stanford UniversityVerified email at stanford.edu
Baris AtaProfessorVerified email at ChicagoBooth.edu
Mark S. SquillanteMathematical Sciences Department, IBM ResearchVerified email at us.ibm.com
Soumyadip GhoshIBM ResearchVerified email at us.ibm.com
Yewen FanPhD student, Carnegie Mellon UniversityVerified email at andrew.cmu.edu
San GultekinMetaVerified email at columbia.edu
Peter W. GlynnProfessor of Management Science and EngineeringVerified email at stanford.edu
Xinyun ChenChinese University of Hong Kong, ShenzhenVerified email at cuhk.edu.cn
Chenxu LiGuanghua School of Management, Peking UniversityVerified email at gsm.pku.edu.cn
Dachuan ChenSchool of Economics, Singapore Management UniversityVerified email at smu.edu.sg
Kun ZhangCarnegie Mellon University & Mohamed bin Zayed University of Artificial Intelligence (MBZUAI)Verified email at cmu.edu
Zeyu ZhengUniversity of California BerkeleyVerified email at berkeley.edu

Nian Si

HKUST

Verified email at ust.hk - Homepage

Applied Probability Experimental Design Causal Inference


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Confidence regions in Wasserstein distributionally robust estimation J Blanchet, K Murthy, N Si Biometrika 109 (2), 295-315, 2022	71	2022
Distributionally robust policy evaluation and learning in offline contextual bandits N Si, F Zhang, Z Zhou, J Blanchet International Conference on Machine Learning, 8884-8894, 2020	65	2020
Distributionally robust batch contextual bandits N Si, F Zhang, Z Zhou, J Blanchet Management Science 69 (10), 5772-5793, 2023	40	2023
Testing group fairness via optimal transport projections N Si, K Murthy, J Blanchet, VA Nguyen International Conference on Machine Learning, 9649-9659, 2021	29	2021
A finite sample complexity bound for distributionally robust q-learning S Wang, N Si, J Blanchet, Z Zhou International Conference on Artificial Intelligence and Statistics, 3370-3398, 2023	27	2023
Robust bayesian classification using an optimistic score ratio VA Nguyen, N Si, J Blanchet International Conference on Machine Learning, 7327-7337, 2020	16	2020
Quantifying the empirical Wasserstein distance to a set of measures: Beating the curse of dimensionality N Si, J Blanchet, S Ghosh, M Squillante Advances in Neural Information Processing Systems 33, 21260-21270, 2020	15	2020
On the foundation of distributionally robust reinforcement learning S Wang, N Si, J Blanchet, Z Zhou arXiv preprint arXiv:2311.09018, 2023	12	2023
Sample complexity of variance-reduced distributionally robust Q-learning S Wang, N Si, J Blanchet, Z Zhou Journal of Machine Learning Research 25 (341), 1-77, 2024	10	2024
Optimal bidding and experimentation for multi-layer auctions in online advertising N Si, S Gultekin, J Blanchet, A Flores Available at SSRN 4358914, 2023	10	2023
Efficient steady-state simulation of high-dimensional stochastic networks J Blanchet, X Chen, N Si, PW Glynn Stochastic Systems 11 (2), 174-192, 2021	7	2021
Optimal uncertainty size in distributionally robust inverse covariance estimation J Blanchet, N Si Operations Research Letters 47 (6), 618-621, 2019	7	2019
Seller-side experiments under interference induced by feedback loops in two-sided platforms Z Zhu, Z Cai, L Zheng, N Si arXiv preprint arXiv:2401.15811, 2024	5	2024
Efficient computation of the likelihood expansions for diffusion models C Li, Y An, D Chen, Q Lin, N Si IIE Transactions 48 (12), 1156-1171, 2016	5	2016
Singular control of (reflected) Brownian motion: a computational method suitable for queueing applications B Ata, JM Harrison, N Si Queueing Systems, 1-37, 2024	4	2024
Calibration Matters: Tackling Maximization Bias in Large-scale Advertising Recommendation Systems Y Fan, N Si, K Zhang arXiv preprint arXiv:2205.09809, 2022	4	2022
Tackling Interference Induced by Data Training Loops in A/B Tests: A Weighted Training Approach N Si arXiv preprint arXiv:2310.17496, 2023	3	2023
Drift control of high-dimensional rbm: a computational method based on neural networks B Ata, JM Harrison, N Si arXiv preprint arXiv:2309.11651, 2023	3	2023
Experimental design in one-sided matching platforms C Weng, X Lei, N Si Available at SSRN 4890353, 2024	2	2024
Statistical Learning of Distributionally Robust Stochastic Control in Continuous State Spaces S Wang, N Si, J Blanchet, Z Zhou arXiv preprint arXiv:2406.11281, 2024	1	2024

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