Edouard Oyallon | DeepAI

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∙ 06/14/2023

A^2CiD^2: Accelerating Asynchronous Communication in Decentralized Deep Learning

Distributed training of Deep Learning models has been critical to many r...

0 Adel Nabli, et al. ∙

∙ 06/12/2023

Can Forward Gradient Match Backpropagation?

Forward Gradients - the idea of using directional derivatives in forward...

0 Louis Fournier, et al. ∙

∙ 06/06/2023

Guiding The Last Layer in Federated Learning with Pre-Trained Models

Federated Learning (FL) is an emerging paradigm that allows a model to b...

0 Gwen Legate, et al. ∙

∙ 07/26/2022

DADAO: Decoupled Accelerated Decentralized Asynchronous Optimization for Time-Varying Gossips

DADAO is a novel decentralized asynchronous stochastic algorithm to mini...

0 Adel Nabli, et al. ∙

∙ 07/18/2022

Why do tree-based models still outperform deep learning on tabular data?

While deep learning has enabled tremendous progress on text and image da...

3 Leo Grinsztajn, et al. ∙

∙ 07/06/2022

On Non-Linear operators for Geometric Deep Learning

This work studies operators mapping vector and scalar fields defined ove...

0 Grégoire Sergeant-Perthuis, et al. ∙

∙ 01/28/2022

Gradient Masked Averaging for Federated Learning

Federated learning is an emerging paradigm that permits a large number o...

0 Irene Tenison, et al. ∙

∙ 07/27/2021

Deep Reinforcement Learning for L3 Slice Localization in Sarcopenia Assessment

Sarcopenia is a medical condition characterized by a reduction in muscle...

12 Othmane Laousy, et al. ∙

∙ 06/11/2021

Decoupled Greedy Learning of CNNs for Synchronous and Asynchronous Distributed Learning

A commonly cited inefficiency of neural network training using back-prop...

0 Eugene Belilovsky, et al. ∙

∙ 01/19/2021

The Unreasonable Effectiveness of Patches in Deep Convolutional Kernels Methods

A recent line of work showed that various forms of convolutional kernel ...

0 Louis Thiry, et al. ∙

∙ 06/10/2020

Interferometric Graph Transform: a Deep Unsupervised Graph Representation

We propose the Interferometric Graph Transform (IGT), which is a new cla...

0 Edouard Oyallon, et al. ∙

∙ 01/23/2019

Decoupled Greedy Learning of CNNs

A commonly cited inefficiency of neural network training by back-propaga...

0 Eugene Belilovsky, et al. ∙

∙ 12/29/2018

Greedy Layerwise Learning Can Scale to ImageNet

Shallow supervised 1-hidden layer neural networks have a number of favor...

0 Eugene Belilovsky, et al. ∙

∙ 12/28/2018

Kymatio: Scattering Transforms in Python

The wavelet scattering transform is an invariant signal representation s...

12 Mathieu Andreux, et al. ∙

∙ 09/27/2018

Compressing the Input for CNNs with the First-Order Scattering Transform

We study the first-order scattering transform as a candidate for reducin...

0 Edouard Oyallon, et al. ∙

∙ 09/17/2018

Scattering Networks for Hybrid Representation Learning

Scattering networks are a class of designed Convolutional Neural Network...

5 Edouard Oyallon, et al. ∙

∙ 06/01/2018

Nonlinear Acceleration of CNNs

The Regularized Nonlinear Acceleration (RNA) algorithm is an acceleratio...

2 Damien Scieur, et al. ∙

∙ 05/24/2018

Nonlinear Acceleration of Deep Neural Networks

Regularized nonlinear acceleration (RNA) is a generic extrapolation sche...

2 Damien Scieur, et al. ∙

∙ 02/20/2018

i-RevNet: Deep Invertible Networks

It is widely believed that the success of deep convolutional networks is...

0 Jörn-Henrik Jacobsen, et al. ∙

∙ 03/27/2017

Scaling the Scattering Transform: Deep Hybrid Networks

We use the scattering network as a generic and fixed ini-tialization of ...

0 Edouard Oyallon, et al. ∙

∙ 03/12/2017

Multiscale Hierarchical Convolutional Networks

Deep neural network algorithms are difficult to analyze because they lac...

0 Jörn-Henrik Jacobsen, et al. ∙

∙ 03/06/2017

Building a Regular Decision Boundary with Deep Networks

In this work, we build a generic architecture of Convolutional Neural Ne...

0 Edouard Oyallon, et al. ∙

∙ 12/30/2014

Deep Roto-Translation Scattering for Object Classification

Dictionary learning algorithms or supervised deep convolution networks h...

0 Edouard Oyallon, et al. ∙

∙ 12/20/2013

Generic Deep Networks with Wavelet Scattering

We introduce a two-layer wavelet scattering network, for object classifi...

0 Edouard Oyallon, et al. ∙

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