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cs.LG2026
Inverse Reinforcement Learning without an Optimal Demonstrator: A Feasible Reward Set Approach
Kihyun Kim, Shripad Deshmukh, Nikos Vlassis +1
Inverse reinforcement learning (IRL) typically assumes demonstrations from a single optimal demonstrator, but in many applications data come from multiple imperfect demonstrators w…
cs.LG2024
A Unified Linear Programming Framework for Offline Reward Learning from Human Demonstrations and Feedback
Kihyun Kim, Jiawei Zhang, Asuman Ozdaglar +1
Inverse Reinforcement Learning (IRL) and Reinforcement Learning from Human Feedback (RLHF) are pivotal methodologies in reward learning, which involve inferring and shaping the und…
cs.LG2019
Generative Autoregressive Networks for 3D Dancing Move Synthesis from Music
Hyemin Ahn, Jaehun Kim, Kihyun Kim +1
This paper proposes a framework which is able to generate a sequence of three-dimensional human dance poses for a given music. The proposed framework consists of three components:…