Nian Si - RankMe

36 papers A* 6A 3Misc 1Journal 26

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Achieving ϵ CoRR Zijun Chen, Zaiwei Chen, Nian Si, Shengbo Wang
2026	J	`jnl`	Learning Sequential Decisions from Multiple Sources via Group-Robust Markov Decision Processes. CoRR Mingyuan Xu, Zongqi Xia, Tianxi Cai, Doudou Zhou, Nian Si
2026	J	`jnl`	Non-Rectangular Average-Reward Robust MDPs: Optimal Policies and Their Transient Values. CoRR Shengbo Wang, Nian Si
2025	J	`jnl`	Bellman Optimality of Average-Reward Robust Markov Decision Processes with a Constant Gain. CoRR Shengbo Wang, Nian Si
2025	A*	`conf`	Knowledge-Guided Wasserstein Distributionally Robust Optimization. ICML Zitao Wang, Ziyuan Wang, Molei Liu, Nian Si
2025	J	`jnl`	Knowledge-Guided Wasserstein Distributionally Robust Optimization. CoRR Zitao Wang, Ziyuan Wang, Molei Liu, Nian Si
2025	J	`jnl`	Near-Optimal Sample Complexities of Divergence-based S-rectangular Distributionally Robust Reinforcement Learning. CoRR Zhenghao Li, Shengbo Wang, Nian Si
2025	J	`jnl`	Representation-Aware Distributionally Robust Optimization: A Knowledge Transfer Framework. CoRR Zitao Wang, Nian Si, Molei Liu
2025	J	`jnl`	Sample Complexity of Distributionally Robust Average-Reward Reinforcement Learning. CoRR Zijun Chen, Shengbo Wang, Nian Si
2025	A	`conf`	ScoreFusion: Fusing Score-based Generative Models via Kullback-Leibler Barycenters. AISTATS Hao Liu, Junze Ye, Jose H. Blanchet, Nian Si
2025	A	`conf`	Statistical Learning of Distributionally Robust Stochastic Control in Continuous State Spaces. AISTATS Shengbo Wang, Nian Si, Jose H. Blanchet, Zhengyuan Zhou
2024	J	`jnl`	Calibration-then-Calculation: A Variance Reduced Metric Framework in Deep Click-Through Rate Prediction Models. CoRR Yewen Fan, Nian Si, Xiangchen Song, Kun Zhang
2024	J	`jnl`	Sample Complexity of Variance-Reduced Distributionally Robust Q-Learning. J. Mach. Learn. Res. Shengbo Wang, Nian Si, Jose H. Blanchet, Zhengyuan Zhou
2024	J	`jnl`	ScoreFusion: fusing score-based generative models via Kullback-Leibler barycenters. CoRR Hao Liu, Junze Ye, Jose H. Blanchet, Nian Si
2024	J	`jnl`	Seller-Side Experiments under Interference Induced by Feedback Loops in Two-Sided Platforms. CoRR Zhihua Zhu, Zheng Cai, Liang Zheng, Nian Si
2024	J	`jnl`	Singular control of (reflected) Brownian motion: a computational method suitable for queueing applications. Queueing Syst. Theory Appl. Baris Ata, J. Michael Harrison, Nian Si
2024	J	`jnl`	Statistical Learning of Distributionally Robust Stochastic Control in Continuous State Spaces. CoRR Shengbo Wang, Nian Si, Jose H. Blanchet, Zhengyuan Zhou
2023	A	`conf`	A Finite Sample Complexity Bound for Distributionally Robust Q-learning. AISTATS Shengbo Wang, Nian Si, José H. Blanchet, Zhengyuan Zhou
2023	J	`jnl`	A Finite Sample Complexity Bound for Distributionally Robust Q-learning. CoRR Shengbo Wang, Nian Si, Jose H. Blanchet, Zhengyuan Zhou
2023	Misc	`conf`	A Preliminary Study of Regularization Framework for Constructing Task-Specific Simulators. WSC Dilara Aykanat, Zeyu Zheng, Nian Si
2023	A*	`conf`	Calibration Matters: Tackling Maximization Bias in Large-scale Advertising Recommendation Systems. ICLR Yewen Fan, Nian Si, Kun Zhang
2023	J	`jnl`	Distributionally Robust Batch Contextual Bandits. Manag. Sci. Nian Si, Fan Zhang, Zhengyuan Zhou, Jose H. Blanchet
2023	J	`jnl`	Drift Control of High-Dimensional RBM: A Computational Method Based on Neural Networks. CoRR Baris Ata, J. Michael Harrison, Nian Si
2023	J	`jnl`	On the Foundation of Distributionally Robust Reinforcement Learning. CoRR Shengbo Wang, Nian Si, Jose H. Blanchet, Zhengyuan Zhou
2023	J	`jnl`	Sample Complexity of Variance-reduced Distributionally Robust Q-learning. CoRR Shengbo Wang, Nian Si, Jose H. Blanchet, Zhengyuan Zhou
2023	J	`jnl`	Singular Control of (Reflected) Brownian Motion: A Computational Method Suitable for Queueing Applications. CoRR Baris Ata, J. Michael Harrison, Nian Si
2023	J	`jnl`	Tackling Interference Induced by Data Training Loops in A/B Tests: A Weighted Training Approach. CoRR Nian Si
2022	J	`jnl`	Calibration Matters: Tackling Maximization Bias in Large-scale Advertising Recommendation Systems. CoRR Yewen Fan, Nian Si, Kun Zhang
2021	A*	`conf`	Testing Group Fairness via Optimal Transport Projections. ICML Nian Si, Karthyek Murthy, Jose H. Blanchet, Viet Anh Nguyen
2021	J	`jnl`	Testing Group Fairness via Optimal Transport Projections. CoRR Nian Si, Karthyek Murthy, Jose H. Blanchet, Viet Anh Nguyen
2020	J	`jnl`	Distributional Robust Batch Contextual Bandits. CoRR Nian Si, Fan Zhang, Zhengyuan Zhou, Jose H. Blanchet
2020	A*	`conf`	Distributionally Robust Policy Evaluation and Learning in Offline Contextual Bandits. ICML Nian Si, Fan Zhang, Zhengyuan Zhou, Jose H. Blanchet
2020	A*	`conf`	Quantifying the Empirical Wasserstein Distance to a Set of Measures: Beating the Curse of Dimensionality. NeurIPS Nian Si, Jose H. Blanchet, Soumyadip Ghosh, Mark S. Squillante
2020	A*	`conf`	Robust Bayesian Classification Using An Optimistic Score Ratio. ICML Viet Anh Nguyen, Nian Si, Jose H. Blanchet
2020	J	`jnl`	Robust Bayesian Classification Using an Optimistic Score Ratio. CoRR Viet Anh Nguyen, Nian Si, Jose H. Blanchet
2019	J	`jnl`	Optimal uncertainty size in distributionally robust inverse covariance estimation. Oper. Res. Lett. Jose H. Blanchet, Nian Si