Jaeuk Shin

According to our database, Jaeuk Shin authored at least 7 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Control of Fab Lifters via Deep Reinforcement Learning: A Semi-MDP Approach.

Giho Kim, Jaeuk Shin, Gihun Kim, Joonrak Kim, Insoon Yang

IEEE Trans Autom. Sci. Eng., October, 2024

Multiparametric Analysis of Multi-Task Markov Decision Processes: Structure, Invariance, and Reducibility.

Jaeuk Shin, Insoon Yang

IEEE Control. Syst. Lett., 2024

Anderson acceleration for partially observable Markov decision processes: A maximum entropy approach.

Mingyu Park, Jaeuk Shin, Insoon Yang

Autom., 2024

On task-relevant loss functions in meta-reinforcement learning.

Jaeuk Shin, Giho Kim, Howon Lee, Joonho Han, Insoon Yang

Proceedings of the 6th Annual Learning for Dynamics & Control Conference, 2024

2023

On Task-Relevant Loss Functions in Meta-Reinforcement Learning and Online LQR.

Jaeuk Shin, Giho Kim, Howon Lee, Joonho Han, Insoon Yang

CoRR, 2023

2022

Infusing Model Predictive Control Into Meta-Reinforcement Learning for Mobile Robots in Dynamic Environments.

Jaeuk Shin, Astghik Hakobyan, Mingyu Park, Yeoneung Kim, Gihun Kim, Insoon Yang

IEEE Robotics Autom. Lett., 2022

2021

Hamilton-Jacobi Deep Q-Learning for Deterministic Continuous-Time Systems with Lipschitz Continuous Controls.

Jeongho Kim, Jaeuk Shin, Insoon Yang

J. Mach. Learn. Res., 2021