Search Results for author: Nathan Grinsztajn

Found 7 papers, 1 papers with code

Better state exploration using action sequence equivalence

no code implementations29 Sep 2021 Nathan Grinsztajn, Toby Johnstone, Johan Ferret, Philippe Preux

Incorporating prior knowledge in reinforcement learning algorithms is mainly an open question.

reinforcement-learning

Interferometric Graph Transform for Community Labeling

no code implementations4 Jun 2021 Nathan Grinsztajn, Louis Leconte, Philippe Preux, Edouard Oyallon

We present a new approach for learning unsupervised node representations in community graphs.

Low-Rank Projections of GCNs Laplacian

no code implementations ICLR Workshop GTRL 2021 Nathan Grinsztajn, Philippe Preux, Edouard Oyallon

In this work, we study the behavior of standard models for community detection under spectral manipulations.

Community Detection

A spectral perspective on GCNs

no code implementations1 Jan 2021 Nathan Grinsztajn, Philippe Preux, Edouard Oyallon

In this work, we study the behavior of standard GCNs under spectral manipulations.

Geometric Deep Reinforcement Learning for Dynamic DAG Scheduling

1 code implementation9 Nov 2020 Nathan Grinsztajn, Olivier Beaumont, Emmanuel Jeannot, Philippe Preux

In this paper, we propose a reinforcement learning approach to solve a realistic scheduling problem, and apply it to an algorithm commonly executed in the high performance computing community, the Cholesky factorization.

Combinatorial Optimization reinforcement-learning

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