Optimal uncertainty size in distributionally robust inverse covariance estimation. - Jose H. Blanchet; Nian Si (Oper. Res. Lett., 2019)

Robust Bayesian Classification Using An Optimistic Score Ratio. - Viet Anh Nguyen; Nian Si; Jose H. Blanchet (ICML, 2020)

Distributionally Robust Policy Evaluation and Learning in Offline Contextual Bandits. - Nian Si; Fan Zhang 059; Zhengyuan Zhou; Jose H. Blanchet (ICML, 2020)

Quantifying the Empirical Wasserstein Distance to a Set of Measures: Beating the Curse of Dimensionality. - Nian Si; Jose H. Blanchet; Soumyadip Ghosh; Mark S. Squillante (NeurIPS, 2020)

Distributional Robust Batch Contextual Bandits. - Nian Si; Fan Zhang 059; Zhengyuan Zhou; Jose H. Blanchet (CoRR, 2020)

Testing Group Fairness via Optimal Transport Projections. - Nian Si; Karthyek Murthy; Jose H. Blanchet; Viet Anh Nguyen (ICML, 2021)

A Finite Sample Complexity Bound for Distributionally Robust Q-learning. - Shengbo Wang; Nian Si; José H. Blanchet; Zhengyuan Zhou (AISTATS, 2023)

Calibration Matters: Tackling Maximization Bias in Large-scale Advertising Recommendation Systems. - Yewen Fan; Nian Si; Kun Zhang 001 (ICLR, 2023)

A Preliminary Study of Regularization Framework for Constructing Task-Specific Simulators. - Dilara Aykanat; Zeyu Zheng; Nian Si (WSC, 2023)

Sample Complexity of Variance-reduced Distributionally Robust Q-learning. - Shengbo Wang; Nian Si; Jose H. Blanchet; Zhengyuan Zhou (CoRR, 2023)

Drift Control of High-Dimensional RBM: A Computational Method Based on Neural Networks. - Baris Ata; J. Michael Harrison 001; Nian Si (CoRR, 2023)

Tackling Interference Induced by Data Training Loops in A/B Tests: A Weighted Training Approach. - Nian Si (CoRR, 2023)

On the Foundation of Distributionally Robust Reinforcement Learning. - Shengbo Wang; Nian Si; Jose H. Blanchet; Zhengyuan Zhou (CoRR, 2023)

Distributionally Robust Batch Contextual Bandits. - Nian Si; Fan Zhang 059; Zhengyuan Zhou; Jose H. Blanchet (Manag. Sci., 2023)

Seller-Side Experiments under Interference Induced by Feedback Loops in Two-Sided Platforms. - Zhihua Zhu; Zheng Cai; Liang Zheng; Nian Si (CoRR, 2024)

Calibration-then-Calculation: A Variance Reduced Metric Framework in Deep Click-Through Rate Prediction Models. - Yewen Fan; Nian Si; Xiangchen Song; Kun Zhang 001 (CoRR, 2024)

Singular control of (reflected) Brownian motion: a computational method suitable for queueing applications. - Baris Ata; J. Michael Harrison 001; Nian Si (Queueing Syst. Theory Appl., 2024)

ScoreFusion: Fusing Score-based Generative Models via Kullback-Leibler Barycenters. - Hao Liu; Junze Ye; Jose H. Blanchet; Nian Si (AISTATS, 2025)

Statistical Learning of Distributionally Robust Stochastic Control in Continuous State Spaces. - Shengbo Wang; Nian Si; Jose H. Blanchet; Zhengyuan Zhou (AISTATS, 2025)

Knowledge-Guided Wasserstein Distributionally Robust Optimization. - Zitao Wang; Ziyuan Wang; Molei Liu; Nian Si (CoRR, 2025)

Sample Complexity of Distributionally Robust Average-Reward Reinforcement Learning. - Zijun Chen; Shengbo Wang; Nian Si (CoRR, 2025)

Near-Optimal Sample Complexities of Divergence-based S-rectangular Distributionally Robust Reinforcement Learning. - Zhenghao Li; Shengbo Wang; Nian Si (CoRR, 2025)