3 papers
cs.LG2026
Reward Transfer from Inverse Reinforcement Learning: A Coupled Minimax Approach
Guang-Yuan Hao, Lars van der Laan, Aurélien Bibaut +1
We study the transfer of rewards learned using inverse reinforcement learning from expert demonstrations in one environment to reinforcement learning in a new, different environmen…
cs.LG2019
DSRGAN: Explicitly Learning Disentangled Representation of Underlying Structure and Rendering for Image Generation without Tuple Supervision
Guang-Yuan Hao, Hong-Xing Yu, Wei-Shi Zheng
We focus on explicitly learning disentangled representation for natural image generation, where the underlying spatial structure and the rendering on the structure can be independe…
cs.LG2018
MIXGAN: Learning Concepts from Different Domains for Mixture Generation
Guang-Yuan Hao, Hong-Xing Yu, Wei-Shi Zheng
In this work, we present an interesting attempt on mixture generation: absorbing different image concepts (e.g., content and style) from different domains and thus generating a new…