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NN-Steiner: A Mixed Neural-algorithmic Approach for the Rectilinear Steiner Minimum Tree Problem
On the methodology front, we propose NN-Steiner, which is a novel mixed neural-algorithmic framework for computing RSMTs that leverages the celebrated PTAS algorithmic framework of Arora to solve this problem (and other geometric optimization problems).
Flexible Multiple-Objective Reinforcement Learning for Chip Placement
Recently, successful applications of reinforcement learning to chip placement have emerged.
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