no code implementations • NeurIPS 2021 • HyeongJoo Hwang, Geon-Hyeong Kim, Seunghoon Hong, Kee-Eung Kim
Multi-View Representation Learning (MVRL) aims to discover a shared representation of observations from different views with the complex underlying correlation.
no code implementations • ICLR 2022 • Geon-Hyeong Kim, Seokin Seo, Jongmin Lee, Wonseok Jeon, HyeongJoo Hwang, Hongseok Yang, Kee-Eung Kim
We consider offline imitation learning (IL), which aims to mimic the expert's behavior from its demonstration without further interaction with the environment.
2 code implementations • NeurIPS 2020 • HyeongJoo Hwang, Geon-Hyeong Kim, Seunghoon Hong, Kee-Eung Kim
Grounded in information theory, we cast the simultaneous learning of domain-invariant and domain-specific representations as a joint objective of multiple information constraints, which does not require adversarial training or gradient reversal layers.