Decoupled Greedy Learning of CNNs for Synchronous and Asynchronous Distributed Learning

no code implementations • 11 Jun 2021 • Eugene Belilovsky, Louis Leconte, Lucas Caccia, Michael Eickenberg, Edouard Oyallon

With the use of a replay buffer we show that this approach can be extended to asynchronous settings, where modules can operate and continue to update with possibly large communication delays.

Image Classification Quantization

Interferometric Graph Transform for Community Labeling

no code implementations • 4 Jun 2021 • Nathan Grinsztajn, Louis Leconte, Philippe Preux, Edouard Oyallon

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

$\texttt{DoStoVoQ}$: Doubly Stochastic Voronoi Vector Quantization SGD for Federated Learning

no code implementations • NeurIPS 2021 • Louis Leconte, Aymeric Dieuleveut, Edouard Oyallon, Eric Moulines, Gilles Pages

The growing size of models and datasets have made distributed implementation of stochastic gradient descent (SGD) an active field of research.

Federated Learning Quantization