Publications and Preprints

Preprint and Under Review

• Hedging Complexity in Generalization via a Parametric Distributionally Robust Optimization Framework
  Garud Iyengar, Henry Lam, Tianyu Wang^*
  Under revison by Management Science.

  Preliminary version appeared in AISTATS 2023.

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

• Rethinking Distribution Shifts: Empirical Analysis and Inductive Modeling for Tabular Data
  Jiashuo Liu⁺, Tianyu Wang⁺, Peng Cui, Hongseok Namkoong
  

  Preliminary version appeared in NeurIPS 2023.

• Contextual Optimization under Covariate Shift: A Robust Approach by Intersecting Wasserstein Balls
  Tianyu Wang, Ningyuan Chen, and Chun Wang
  

  Preliminary version: Distributionally Robust Prescriptive Analytics with Wasserstein Distance

Publications

• Is Cross-validation the Gold Standard to Estimate Out-of-sample Model Performance?
  Garud Iyengar, Henry Lam, Tianyu Wang^*
  

  Advances in Neural Information Processing Systems (NeurIPS) 2024.

• Geometry-Calibrated DRO: Combating Over-Pessimism with Free Energy Implications
  Jiashuo Liu, Jiayun Wu, Tianyu Wang, Hao Zou, Peng Cui
  International Conference on Machine Learning (ICML), 2024.
  Short version appeared in 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, 25(5): 1779 - 1795, 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