Working Papers
"Bayesian Optimization in Language space: An Eval-Efficient AI Self-Improvement Framework", by Enoch H. Kang* and Hema Yoganarasimhan, 2025
Stanford AI & Marketing: New Methods and New Risks Conference
Columbia AI/ML conference
"Stability and generalization for Bellman residuals", Enoch H. Kang and Kyoungseok Jang, 2025
"Empirical risk minimization for Inverse RL and Dynamic Discrete Choice models" by Enoch H. Kang*, Lalit Jain, and Hema Yoganarasimhan, 2025 (minor revision, Operations Research)
Accepted in the main track, Economics and Computation 2025, [arXiv 2502.14131]
Invited tutorial talk (John Rust's session, guest lecturer), Econometric Society Summer School in Dynamic Structural Econometrics 2025 (YouTube Link) (Slides)
The 2025 World Congress of the Econometric Society (ESWC 2025)
UBC econometric lunch seminar
"In Silico Experimentation: a new paradigm for method testing", working manuscript
"Reasonably reasoning AI agents avoid game-theoretic failures in zero-shot, provably", working manuscript
"Fast globally convergent gradient-based offline reinforcement learning", working manuscript
Published Papers
"Is O (log N) practical? Near-Equivalence Between Delay Robustness and Bounded Regret in Bandits and RL", Enoch H. Kang* and P. R. Kumar, NeurIPS 2024, Paper link
NeurIPS 2023 Adaptive Experimentation and Active Learning in the Real World (ReALML) workshop
"Recommender system as an exploration coordinator: a bounded O(1) regret algorithm for large platforms", Enoch H Kang, P. R. Kumar, Allerton 2023, Paper Link
ICML 2022 Adaptive Experimentation and Active Learning in the Real World (ReALML) workshop
RecSys 2022 Causality, Counterfactuals, Sequential Decision-Making & Reinforcement Learning workshop (Selected as the Long Oral presentation)
"Learning NP-Hard Multi-Agent Assignment Planning using GNN: Inference on a Random Graph and Provable Auction-Fitted Q-learning", Enoch H. Kang, Taehwan Kwon, James R. Morrison, and Jinkyoo Park, NeurIPS 2022, Paper Link
ICML GRL+: novel applications, best paper runner up (Oral presentation link)
Informs Annual Meeting 2020 (Contributed Long Oral talk)