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cs.LG2025
CORE: Constraint-Aware One-Step Reinforcement Learning for Simulation-Guided Neural Network Accelerator Design
Yifeng Xiao, Yurong Xu, Ning Yan +2
Simulation-based design space exploration (DSE) aims to efficiently optimize high-dimensional structured designs under complex constraints and expensive evaluation costs. Existing…
eess.SY2025
Inverse Design in Distributed Circuits Using Single-Step Reinforcement Learning
Jiayu Li, Masood Mortazavi, Ning Yan +2
The goal of inverse design in distributed circuits is to generate near-optimal designs that meet a desirable transfer function specification. Existing design exploration methods us…