An Optimization-based Algorithm for Non-stationary Kernel Bandits without Prior Knowledge. - Kihyuk Hong; Yuhang Li; Ambuj Tewari (AISTATS, 2023)

A Primal-Dual-Critic Algorithm for Offline Constrained Reinforcement Learning. - Kihyuk Hong; Yuhang Li; Ambuj Tewari (AISTATS, 2024)

A Primal-Dual Algorithm for Offline Constrained Reinforcement Learning with Linear MDPs. - Kihyuk Hong; Ambuj Tewari (ICML, 2024)

A Primal-Dual Algorithm for Offline Constrained Reinforcement Learning with Low-Rank MDPs. - Kihyuk Hong; Ambuj Tewari (CoRR, 2024)

Provably Efficient Reinforcement Learning for Infinite-Horizon Average-Reward Linear MDPs. - Kihyuk Hong; Yufan Zhang; Ambuj Tewari (CoRR, 2024)

Learning Infinite-Horizon Average-Reward Linear Mixture MDPs of Bounded Span. - Woojin Chae; Kihyuk Hong; Yufan Zhang; Ambuj Tewari; Dabeen Lee (AISTATS, 2025)

Reinforcement Learning for Infinite-Horizon Average-Reward Linear MDPs via Approximation by Discounted-Reward MDPs. - Kihyuk Hong; Woojin Chae; Yufan Zhang; Dabeen Lee; Ambuj Tewari (AISTATS, 2025)

A Computationally Efficient Algorithm for Infinite-Horizon Average-Reward Linear MDPs. - Kihyuk Hong; Ambuj Tewari (CoRR, 2025)

Generator-Mediated Bandits: Thompson Sampling for GenAI-Powered Adaptive Interventions. - Marc Brooks; Gabriel Durham; Kihyuk Hong; Ambuj Tewari (CoRR, 2025)

Offline Constrained Reinforcement Learning under Partial Data Coverage. - Kihyuk Hong; Ambuj Tewari (CoRR, 2025)