Nian Si

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Jose BlanchetStanford UniversityDirección de correo verificada de stanford.edu
Zhengyuan ZhouDept of Technology, Operations and Statistics at NYU SternDirección de correo verificada de stern.nyu.edu
Shengbo WangPh.D. candidate, Stanford UniversityDirección de correo verificada de stanford.edu
Fan ZhangManagement Science and Engineering, Stanford UniversityDirección de correo verificada de stanford.edu
Karthyek MurthySingapore University of Technology and DesignDirección de correo verificada de sutd.edu.sg
Viet Anh NguyenThe Chinese University of Hong KongDirección de correo verificada de cuhk.edu.hk
J. Michael HarrisonProfessor of Management, Stanford UniversityDirección de correo verificada de stanford.edu
Baris AtaProfessorDirección de correo verificada de ChicagoBooth.edu
Mark S. SquillanteMathematical Sciences Department, IBM ResearchDirección de correo verificada de us.ibm.com
Soumyadip GhoshIBM ResearchDirección de correo verificada de us.ibm.com
Yewen FanPhD student, Carnegie Mellon UniversityDirección de correo verificada de andrew.cmu.edu
San GultekinMetaDirección de correo verificada de columbia.edu
Peter W. GlynnProfessor of Management Science and EngineeringDirección de correo verificada de stanford.edu
Xinyun ChenChinese University of Hong Kong, ShenzhenDirección de correo verificada de cuhk.edu.cn
Chenxu LiGuanghua School of Management, Peking UniversityDirección de correo verificada de gsm.pku.edu.cn
Dachuan ChenSchool of Economics, Singapore Management UniversityDirección de correo verificada de smu.edu.sg
Kun ZhangCarnegie Mellon University & Mohamed bin Zayed University of Artificial Intelligence (MBZUAI)Dirección de correo verificada de cmu.edu
Zeyu ZhengUniversity of California BerkeleyDirección de correo verificada de berkeley.edu

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Nian Si

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Applied Probability Experimental Design Causal Inference


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
Confidence regions in Wasserstein distributionally robust estimation J Blanchet, K Murthy, N Si Biometrika 109 (2), 295-315, 2022	73	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	67	2020
Distributionally robust batch contextual bandits N Si, F Zhang, Z Zhou, J Blanchet Management Science 69 (10), 5772-5793, 2023	43	2023
Testing group fairness via optimal transport projections N Si, K Murthy, J Blanchet, VA Nguyen International Conference on Machine Learning, 9649-9659, 2021	31	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	28	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	13	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	11	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	6	2024
Tackling Interference Induced by Data Training Loops in A/B Tests: A Weighted Training Approach N Si arXiv preprint arXiv:2310.17496, 2023	5	2023
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
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	4	2023
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
Experimental design in one-sided matching platforms C Weng, X Lei, N Si Available at SSRN 4890353, 2024	3	2024
Selecting the Best Optimizing System N Si, Z Zheng arXiv preprint arXiv:2201.03065, 2022	3	2022

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