Nian Si

According to our database, Nian Si authored at least 19 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Singular control of (reflected) Brownian motion: a computational method suitable for queueing applications.

Baris Ata, J. Michael Harrison, Nian Si

Queueing Syst. Theory Appl., December, 2024

ScoreFusion: fusing score-based generative models via Kullback-Leibler barycenters.

Hao Liu, Junze Ye, Jose H. Blanchet, Nian Si

CoRR, 2024

Statistical Learning of Distributionally Robust Stochastic Control in Continuous State Spaces.

Shengbo Wang, Nian Si, Jose H. Blanchet, Zhengyuan Zhou

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

CoRR, 2024

Seller-Side Experiments under Interference Induced by Feedback Loops in Two-Sided Platforms.

Zhihua Zhu, Zheng Cai, Liang Zheng, Nian Si

CoRR, 2024

2023

Distributionally Robust Batch Contextual Bandits.

Nian Si, Fan Zhang, Zhengyuan Zhou, Jose H. Blanchet

Manag. Sci., October, 2023

On the Foundation of Distributionally Robust Reinforcement Learning.

Shengbo Wang, Nian Si, Jose H. Blanchet, Zhengyuan Zhou

CoRR, 2023

Tackling Interference Induced by Data Training Loops in A/B Tests: A Weighted Training Approach.

Nian Si

CoRR, 2023

Drift Control of High-Dimensional RBM: A Computational Method Based on Neural Networks.

Baris Ata, J. Michael Harrison, Nian Si

CoRR, 2023

Sample Complexity of Variance-reduced Distributionally Robust Q-learning.

Shengbo Wang, Nian Si, Jose H. Blanchet, Zhengyuan Zhou

CoRR, 2023

A Preliminary Study of Regularization Framework for Constructing Task-Specific Simulators.

Dilara Aykanat, Zeyu Zheng, Nian Si

Proceedings of the Winter Simulation Conference, 2023

Calibration Matters: Tackling Maximization Bias in Large-scale Advertising Recommendation Systems.

Yewen Fan, Nian Si, Kun Zhang

Proceedings of the Eleventh International Conference on Learning Representations, 2023

A Finite Sample Complexity Bound for Distributionally Robust Q-learning.

Shengbo Wang, Nian Si, José H. Blanchet, Zhengyuan Zhou

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2021

Testing Group Fairness via Optimal Transport Projections.

Nian Si, Karthyek Murthy, Jose H. Blanchet, Viet Anh Nguyen

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Distributional Robust Batch Contextual Bandits.

Nian Si, Fan Zhang, Zhengyuan Zhou, Jose H. Blanchet

CoRR, 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

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Distributionally Robust Policy Evaluation and Learning in Offline Contextual Bandits.

Nian Si, Fan Zhang, Zhengyuan Zhou, Jose H. Blanchet

Proceedings of the 37th International Conference on Machine Learning, 2020

Robust Bayesian Classification Using An Optimistic Score Ratio.

Viet Anh Nguyen, Nian Si, Jose H. Blanchet

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Optimal uncertainty size in distributionally robust inverse covariance estimation.

Jose H. Blanchet, Nian Si

Oper. Res. Lett., 2019