Seungyub Han

Stochastic Truncation for Multi-Step Off-Policy RL

Policy-labeled Preference Learning: Is Preference Enough for RLHF?

Pareto Optimal Risk-Agnostic Distributional Bandits with Heavy-Tail Rewards

Bellman Unbiasedness: Toward Provably Efficient Distributional Reinforcement Learning with General Value Function Approximation

Bellman Unbiasedness: Toward Provably Efficient Distributional Reinforcement Learning with General Value Function Approximation

Self-Alignment for Offline Safe Reinforcement Learning

Time to Truncate Trajectory: Stochastic Retrace for Multi-step Off-policy Reinforcement Learning