2 papers
cs.LG2026
Dynamic Deep-Reinforcement-Learning Algorithm in Partially Observable Markov Decision Processes
Saki Omi, Hyo-Sang Shin, Namhoon Cho +1
Recent studies have greatly improved reinforcement learning, and an increased interest in real-world implementation has emerged. In many cases, the implementation is challenged by…
math.OC2024
A Passivity-Based Method for Accelerated Convex Optimisation
Namhoon Cho, Hyo-Sang Shin
This study presents a constructive methodology for designing accelerated convex optimisation algorithms in continuous-time domain. The two key enablers are the classical concept of…