4 papers
Neural Variance-aware Dueling Bandits with Deep Representation and Shallow Exploration
Youngmin Oh, Jinje Park, Taejin Paik
We introduce the first variance-aware algorithms for contextual dueling bandits that leverage shallow exploration strategies with neural networks for nonlinear utility approximatio…
Reset & Distill: A Recipe for Overcoming Negative Transfer in Continual Reinforcement Learning
Hongjoon Ahn, Jinu Hyeon, Youngmin Oh +2
We argue that the negative transfer problem occurring when the new task to learn arrives is an important problem that needs not be overlooked when developing effective Continual Re…
PPAAS: PVT and Pareto Aware Analog Sizing via Goal-conditioned Reinforcement Learning
Seunggeun Kim, Ziyi Wang, Sungyoung Lee +4
Device sizing is a critical yet challenging step in analog and mixed-signal circuit design, requiring careful optimization to meet diverse performance specifications. This challeng…
M3: Mamba-assisted Multi-Circuit Optimization via MBRL with Effective Scheduling
Youngmin Oh, Jinje Park, Seunggeun Kim +3
Recent advancements in reinforcement learning (RL) for analog circuit optimization have demonstrated significant potential for improving sample efficiency and generalization across…