Research

Research Papers

Publications

  1. Yichun Hu, Nathan Kallus, Xiaojie Mao. Fast Rates for Contextual Linear Optimization. Management Science, accepted.
  2. Yichun Hu, Nathan Kallus, Xiaojie Mao. Smooth Contextual Bandits: Bridging the Parametric and Non-differentiableRegret Regimes. Operations Research, accepted.
    • Preliminary version appeared in 33rd Conference on Learning Theory (COLT 2020).
    • Finalist, INFORMS Applied Probability Society 2020 Best Student Paper Competition.
  3. Yichun Hu, Nathan Kallus, Masatoshi Uehara. Fast Rates for the Regret of Offline Reinforcement Learning. 34th Conferenceon Learning Theory (COLT 2021).

Under Review

  1. Yichun Hu, Nathan Kallus. DTR Bandit: Learning to Make Response-Adaptive Decisions with Low Regret. Under review.

Workshop Papers

  1. Mia Garrard, Hanson Wang, Benjamin Letham, Shaun Singh, Abbas Kazerouni, Sarah Tan, Zehui Wang, Yin Huang, Yichun Hu, Chad Zhou, Norm Zhou, Eytan Bakshy. Practical Policy Optimization with Personalized Experimentation. NeurIPS 2021 Workshop on Causal Inference Challenges in Sequential Decision Making: Bridging Theory and Practice.

Talks

  • RL Theory Seminar, Virtual, 11/2021
  • INFORMS Annual Meeting, Anaheim, CA, 10/2021
  • 16th INFORMS Workshop on Data Mining and Decision Analytics, Anaheim, CA, 10/2021
  • 34th Annual Conference on Learning Theory (COLT 2021), Boulder, CO, 08/2021
  • INFORMS Annual Meeting, Virtual, 11/2020
  • 15th INFORMS Workshop on Data Mining and Decision Analytics, Virtual, 11/2020
  • 33rd Annual Conference on Learning Theory (COLT 2020), Virtual, 07/2020
  • INFORMS Annual Meeting, Seattle, WA, 10/2019
  • 14th INFORMS Workshop on Data Mining and Decision Analytics, Seattle, WA, 10/2019
  • Cornell ORIE Young Researchers Workshop, Ithaca, NY, 10/2019