Publications and Preprints

Preprint and Under Review

• Geometry-Calibrated DRO: Combating Over-Pessimism with Free Energy Implications
  Jiashuo Liu, Jiayun Wu, Tianyu Wang, Hao Zou, Peng Cui
  

• Optimizer's Information Criterion: Dissecting and Correcting Bias in Data-Driven Optimization
  Garud Iyengar, Henry Lam, Tianyu Wang^*
  

• Hedging Complexity in Generalization via a Parametric Distributionally Robust Optimization Framework
  Garud Iyengar, Henry Lam, Tianyu Wang^*
  Journal version under review

  Preliminary version appeared in AISTATS 2023.

• Contextual Optimization under Covariate Shift: A Doubly Robust Perspective
  Tianyu Wang, Ningyuan Chen, and Chun Wang
  

Publications

• Geometry-Calibrated DRO: Combating Over-Pessimism with Free Energy Implications
  Jiashuo Liu, Jiayun Wu, Tianyu Wang, Hao Zou, Peng Cui
  NeurIPS 2023 Workshop on Distribution Shifts

• On the Need for a Language Describing Distribution Shifts: Illustrations on Tabular Datasets [Code] [Python package]
  Jiashuo Liu⁺, Tianyu Wang⁺, Peng Cui, Hongseok Namkoong
  Advances in Neural Information Processing Systems (NeurIPS) 2023, Datasets and Benchmarks Track.

• Data-Driven Distributionally Robust CVaR Portfolio Optimization Under A Regime-Switching Ambiguity Set [Code]
  Chi Seng Pun, Tianyu Wang, Zhenzhen Yan^*
  Manufacturing and Service Operations Management, Articles in Advance, 2023.

• Hedging against Complexity: Distributionally Robust Optimization with Parametric Approximation [Code]
  Garud Iyengar, Henry Lam, Tianyu Wang^*
  International Conference on Artificial Intelligence and Statistics (AISTATS), 2023.
  Oral presentation, 32/1689 = 1.9% of submissions

• On Data-Driven Multi-Product Pricing [Code]
  Tianyu Wang, Chenye Wu, and Wei Qi
  IEEE Control Systems Letters (L-CSS) (2020): 1687-1692.

  also invited to present in Proc. of American Control Conference (ACC), May 2021.