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2020 – today
- 2024
[j3]Baris Ata, J. Michael Harrison, Nian Si
:
Singular control of (reflected) Brownian motion: a computational method suitable for queueing applications. Queueing Syst. Theory Appl. 108(3): 215-251 (2024)- [i14]Zhihua Zhu, Zheng Cai, Liang Zheng, Nian Si:
Seller-Side Experiments under Interference Induced by Feedback Loops in Two-Sided Platforms. CoRR abs/2401.15811 (2024) - [i13]Yewen Fan, Nian Si, Xiangchen Song, Kun Zhang:
Calibration-then-Calculation: A Variance Reduced Metric Framework in Deep Click-Through Rate Prediction Models. CoRR abs/2401.16692 (2024) - [i12]Shengbo Wang, Nian Si, Jose H. Blanchet, Zhengyuan Zhou:
Statistical Learning of Distributionally Robust Stochastic Control in Continuous State Spaces. CoRR abs/2406.11281 (2024) - [i11]Hao Liu, Junze Ye, Jose H. Blanchet, Nian Si:
ScoreFusion: fusing score-based generative models via Kullback-Leibler barycenters. CoRR abs/2406.19619 (2024) - 2023
- [j2]Nian Si, Fan Zhang, Zhengyuan Zhou, Jose H. Blanchet:
Distributionally Robust Batch Contextual Bandits. Manag. Sci. 69(10): 5772-5793 (2023) - [c7]Shengbo Wang, Nian Si, José H. Blanchet, Zhengyuan Zhou:
A Finite Sample Complexity Bound for Distributionally Robust Q-learning. AISTATS 2023: 3370-3398 - [c6]Yewen Fan, Nian Si, Kun Zhang:
Calibration Matters: Tackling Maximization Bias in Large-scale Advertising Recommendation Systems. ICLR 2023 - [c5]Dilara Aykanat, Zeyu Zheng, Nian Si:
A Preliminary Study of Regularization Framework for Constructing Task-Specific Simulators. WSC 2023: 805-816 - [i10]Shengbo Wang, Nian Si, Jose H. Blanchet, Zhengyuan Zhou:
A Finite Sample Complexity Bound for Distributionally Robust Q-learning. CoRR abs/2302.13203 (2023) - [i9]Shengbo Wang, Nian Si, Jose H. Blanchet, Zhengyuan Zhou:
Sample Complexity of Variance-reduced Distributionally Robust Q-learning. CoRR abs/2305.18420 (2023) - [i8]Baris Ata, J. Michael Harrison, Nian Si:
Drift Control of High-Dimensional RBM: A Computational Method Based on Neural Networks. CoRR abs/2309.11651 (2023) - [i7]Nian Si:
Tackling Interference Induced by Data Training Loops in A/B Tests: A Weighted Training Approach. CoRR abs/2310.17496 (2023) - [i6]Shengbo Wang, Nian Si, Jose H. Blanchet, Zhengyuan Zhou:
On the Foundation of Distributionally Robust Reinforcement Learning. CoRR abs/2311.09018 (2023) - [i5]Baris Ata, J. Michael Harrison, Nian Si:
Singular Control of (Reflected) Brownian Motion: A Computational Method Suitable for Queueing Applications. CoRR abs/2312.11823 (2023) - 2022
- [i4]Yewen Fan, Nian Si, Kun Zhang:
Calibration Matters: Tackling Maximization Bias in Large-scale Advertising Recommendation Systems. CoRR abs/2205.09809 (2022) - 2021
- [c4]Nian Si, Karthyek Murthy, Jose H. Blanchet, Viet Anh Nguyen:
Testing Group Fairness via Optimal Transport Projections. ICML 2021: 9649-9659 - [i3]Nian Si, Karthyek Murthy, Jose H. Blanchet, Viet Anh Nguyen:
Testing Group Fairness via Optimal Transport Projections. CoRR abs/2106.01070 (2021) - 2020
- [c3]Viet Anh Nguyen, Nian Si, Jose H. Blanchet:
Robust Bayesian Classification Using An Optimistic Score Ratio. ICML 2020: 7327-7337 - [c2]Nian Si, Fan Zhang, Zhengyuan Zhou, Jose H. Blanchet:
Distributionally Robust Policy Evaluation and Learning in Offline Contextual Bandits. ICML 2020: 8884-8894 - [c1]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 - [i2]Nian Si, Fan Zhang, Zhengyuan Zhou, Jose H. Blanchet:
Distributional Robust Batch Contextual Bandits. CoRR abs/2006.05630 (2020) - [i1]Viet Anh Nguyen, Nian Si, Jose H. Blanchet:
Robust Bayesian Classification Using an Optimistic Score Ratio. CoRR abs/2007.04458 (2020)
2010 – 2019
- 2019
- [j1]Jose H. Blanchet, Nian Si:
Optimal uncertainty size in distributionally robust inverse covariance estimation. Oper. Res. Lett. 47(6): 618-621 (2019)
Coauthor Index
aka: José H. Blanchet
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