Reinforced Genetic Algorithm Learning for Optimizing Computation Graphs

no code implementations • ICLR 2020 • Aditya Paliwal, Felix Gimeno, Vinod Nair, Yujia Li, Miles Lubin, Pushmeet Kohli, Oriol Vinyals

We present a deep reinforcement learning approach to minimizing the execution cost of neural network computation graphs in an optimizing compiler.

reinforcement-learning Reinforcement Learning (RL) +1

Graph Representations for Higher-Order Logic and Theorem Proving

no code implementations • 24 May 2019 • Aditya Paliwal, Sarah Loos, Markus Rabe, Kshitij Bansal, Christian Szegedy

This paper presents the first use of graph neural networks (GNNs) for higher-order proof search and demonstrates that GNNs can improve upon state-of-the-art results in this domain.

Automated Theorem Proving