NeurIPS 2019
Sun Dec 8th through Sat the 14th, 2019 at Vancouver Convention Center
Paper ID:2191
Title:Learning Generalizable Device Placement Algorithms for Distributed Machine Learning

The paper introduces a new RL-based approach to device placement in computation graphs that relies on using graph embedding neural network instead of RNNs. The reviewers were all impressed by the novelty of the proposed approach, the significance of the empirical results, as well as by the ability of the method to generalize across different tasks. While preparing the final version, please take into account the detailed comments and suggestions mentioned in the reviews.