233 citations · 785 across the 38 of their papers we have counts for
6 papers · 1 filter
Training Signal Design for Sparse Channel Estimation in Intelligent Reflecting Surface-Assisted Millimeter-Wave Communication
Song Noh, Heejung Yu, Youngchul Sung
In this paper, the problem of training signal design for intelligent reflecting surface (IRS)-assisted millimeter-wave (mmWave) communication under a sparse channel model is consid…
A Reinforcement Learning Formulation of the Lyapunov Optimization: Application to Edge Computing Systems with Queue Stability
Sohee Bae, Seungyul Han, Youngchul Sung
In this paper, a deep reinforcement learning (DRL)-based approach to the Lyapunov optimization is considered to minimize the time-average penalty while maintaining queue stability.…
A Maximum Mutual Information Framework for Multi-Agent Reinforcement Learning
Woojun Kim, Whiyoung Jung, Myungsik Cho +1
In this paper, we propose a maximum mutual information (MMI) framework for multi-agent reinforcement learning (MARL) to enable multiple agents to learn coordinated behaviors by reg…
Cross-Domain Imitation Learning with a Dual Structure
Sungho Choi, Seungyul Han, Woojun Kim +1
In this paper, we consider cross-domain imitation learning (CDIL) in which an agent in a target domain learns a policy to perform well in the target domain by observing expert demo…
Diversity Actor-Critic: Sample-Aware Entropy Regularization for Sample-Efficient Exploration
Seungyul Han, Youngchul Sung
In this paper, sample-aware policy entropy regularization is proposed to enhance the conventional policy entropy regularization for better exploration. Exploiting the sample distri…
Population-Guided Parallel Policy Search for Reinforcement Learning
Whiyoung Jung, Giseung Park, Youngchul Sung
In this paper, a new population-guided parallel learning scheme is proposed to enhance the performance of off-policy reinforcement learning (RL). In the proposed scheme, multiple i…