Nian Si

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 23

Top Topics

Continuous State Spaces

Bayesian Classification

Kullback Leibler

Top Venues

Publications

Shengbo Wang, Nian Si, Jose H. Blanchet, Zhengyuan Zhou
Statistical Learning of Distributionally Robust Stochastic Control in Continuous State Spaces. CoRR (2024)
Yewen Fan, Nian Si, Xiangchen Song, Kun Zhang
Calibration-then-Calculation: A Variance Reduced Metric Framework in Deep Click-Through Rate Prediction Models. CoRR (2024)
Hao Liu, Junze Ye, Jose H. Blanchet, Nian Si
ScoreFusion: fusing score-based generative models via Kullback-Leibler barycenters. CoRR (2024)
Zhihua Zhu, Zheng Cai, Liang Zheng, Nian Si
Seller-Side Experiments under Interference Induced by Feedback Loops in Two-Sided Platforms. CoRR (2024)
Nian Si
Tackling Interference Induced by Data Training Loops in A/B Tests: A Weighted Training Approach. CoRR (2023)
Yewen Fan, Nian Si, Kun Zhang
Calibration Matters: Tackling Maximization Bias in Large-scale Advertising Recommendation Systems. ICLR (2023)
Nian Si, Fan Zhang, Zhengyuan Zhou, Jose H. Blanchet
Distributionally Robust Batch Contextual Bandits. Manag. Sci. 69 (10) (2023)
Dilara Aykanat, Zeyu Zheng, Nian Si
A Preliminary Study of Regularization Framework for Constructing Task-Specific Simulators. WSC (2023)
Shengbo Wang, Nian Si, Jose H. Blanchet, Zhengyuan Zhou
On the Foundation of Distributionally Robust Reinforcement Learning. CoRR (2023)
Shengbo Wang, Nian Si, José H. Blanchet, Zhengyuan Zhou
A Finite Sample Complexity Bound for Distributionally Robust Q-learning. AISTATS (2023)
Shengbo Wang, Nian Si, Jose H. Blanchet, Zhengyuan Zhou
Sample Complexity of Variance-reduced Distributionally Robust Q-learning. CoRR (2023)
Baris Ata, J. Michael Harrison, Nian Si
Singular Control of (Reflected) Brownian Motion: A Computational Method Suitable for Queueing Applications. CoRR (2023)
Shengbo Wang, Nian Si, Jose Blanchet, Zhengyuan Zhou
A Finite Sample Complexity Bound for Distributionally Robust Q-learning. CoRR (2023)
Baris Ata, J. Michael Harrison, Nian Si
Drift Control of High-Dimensional RBM: A Computational Method Based on Neural Networks. CoRR (2023)
Yewen Fan, Nian Si, Kun Zhang
Calibration Matters: Tackling Maximization Bias in Large-scale Advertising Recommendation Systems. CoRR (2022)
Nian Si, Karthyek Murthy, Jose H. Blanchet, Viet Anh Nguyen
Testing Group Fairness via Optimal Transport Projections. CoRR (2021)
Nian Si, Karthyek Murthy, Jose H. Blanchet, Viet Anh Nguyen
Testing Group Fairness via Optimal Transport Projections. ICML (2021)
Viet Anh Nguyen, Nian Si, Jose H. Blanchet
Robust Bayesian Classification Using An Optimistic Score Ratio. ICML (2020)
Viet Anh Nguyen, Nian Si, Jose H. Blanchet
Robust Bayesian Classification Using an Optimistic Score Ratio. CoRR (2020)
Nian Si, Jose H. Blanchet, Soumyadip Ghosh, Mark S. Squillante
Quantifying the Empirical Wasserstein Distance to a Set of Measures: Beating the Curse of Dimensionality. NeurIPS (2020)
Nian Si, Fan Zhang, Zhengyuan Zhou, Jose H. Blanchet
Distributional Robust Batch Contextual Bandits. CoRR (2020)
Nian Si, Fan Zhang, Zhengyuan Zhou, Jose H. Blanchet
Distributionally Robust Policy Evaluation and Learning in Offline Contextual Bandits. ICML (2020)
Jose H. Blanchet, Nian Si
Optimal uncertainty size in distributionally robust inverse covariance estimation. Oper. Res. Lett. 47 (6) (2019)