Jaeuk Shin

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 9

Top Topics

Markov Decision Process

Maximum Entropy

Reinforcement Learning

Partially Observable

Top Venues

IEEE Robotics Autom. Lett.

IEEE Control. Syst. Lett.

Publications

Jaeuk Shin, Insoon Yang
Multiparametric Analysis of Multi-Task Markov Decision Processes: Structure, Invariance, and Reducibility. IEEE Control. Syst. Lett. 8 (2024)
Jaeuk Shin, Giho Kim, Howon Lee, Joonho Han, Insoon Yang
On task-relevant loss functions in meta-reinforcement learning. L4DC (2024)
Mingyu Park, Jaeuk Shin, Insoon Yang
Anderson acceleration for partially observable Markov decision processes: A maximum entropy approach. Autom. 163 (2024)
Jaeuk Shin, Giho Kim, Howon Lee, Joonho Han, Insoon Yang
On Task-Relevant Loss Functions in Meta-Reinforcement Learning and Online LQR. CoRR (2023)
Jaeuk Shin, Astghik Hakobyan, Mingyu Park, Yeoneung Kim, Gihun Kim, Insoon Yang
Infusing Model Predictive Control Into Meta-Reinforcement Learning for Mobile Robots in Dynamic Environments. IEEE Robotics Autom. Lett. 7 (4) (2022)
Mingyu Park, Jaeuk Shin, Insoon Yang
Anderson Acceleration for Partially Observable Markov Decision Processes: A Maximum Entropy Approach. CoRR (2022)
Jeongho Kim, Jaeuk Shin, Insoon Yang
Hamilton-Jacobi Deep Q-Learning for Deterministic Continuous-Time Systems with Lipschitz Continuous Controls. J. Mach. Learn. Res. 22 (2021)
Jaeuk Shin, Astghik Hakobyan, Mingyu Park, Yeoneung Kim, Gihun Kim, Insoon Yang
Infusing model predictive control into meta-reinforcement learning for mobile robots in dynamic environments. CoRR (2021)
Jeongho Kim, Jaeuk Shin, Insoon Yang
Hamilton-Jacobi Deep Q-Learning for Deterministic Continuous-Time Systems with Lipschitz Continuous Controls. CoRR (2020)