Edouard Oyallon
20 papers · 2015–2025 · 7 venues · across top CS/AI venues
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🗺️ Taxonomy Completionist (29) 🏃 Academic Marathon · Half 🌍 Conference Polyglot · Silver 🌉 Interdisciplinary Bridge · Bronze 🐣 Hot Topic Early Bird
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Dynamic Duo
(10)
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Conference Pioneer
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Unstoppable · Bronze
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Century Club · Bronze
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Machine Learning
(16)
Deep Learning
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Optimization & Theory · Machine Learning
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Mathematics & Optimization
(5)
Optimization
(4)
Techniques
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Computer Vision
(3)
Learning Types · Deep Learning
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Artificial Intelligence
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Analysis
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Learning Types · Machine Learning
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Keywords
convolutional neural network
(5)
image classification
(4)
representation learning
(3)
neural network training
(2)
accelerated gradient
(2)
neural network
(2)
asynchronous optimization
(2)
decentralized optimization
(2)
distributed optimization
(2)
feature extraction
(2)
distributed training
(2)
greedy learning
(2)
wavelet transform
(1)
image reconstruction
(1)
manifold learning
(1)
distributed learning
(1)
object recognition
(1)
unsupervised learning
(1)
convex optimization
(1)
deep learning
(1)
Papers
Decentralized Asynchronous Optimization with DADAO allows Decoupling and Acceleration
JMLR 2025
DISCO: learning to DISCover an evolution Operator for multi-physics-agnostic prediction
ICML 2025
PETRA: Parallel End-to-end Training with Reversible Architectures
ICLR 2025
A^2CiD^2: Accelerating Asynchronous Communication in Decentralized Deep Learning
NeurIPS 2023
Can Forward Gradient Match Backpropagation?
ICML 2023
DADAO: Decoupled Accelerated Decentralized Asynchronous Optimization
ICML 2023
Guiding The Last Layer in Federated Learning with Pre-Trained Models
NeurIPS 2023
On Non-Linear operators for Geometric Deep Learning
NeurIPS 2022
Why do tree-based models still outperform deep learning on typical tabular data?
NeurIPS 2022
The Unreasonable Effectiveness of Patches in Deep Convolutional Kernels Methods
ICLR 2021
Decoupled Greedy Learning of CNNs
ICML 2020
Interferometric Graph Transform: a Deep Unsupervised Graph Representation
ICML 2020
Kymatio: Scattering Transforms in Python
JMLR 2020
Greedy Layerwise Learning Can Scale To ImageNet
ICML 2019
On Lazy Training in Differentiable Programming
NeurIPS 2019
Compressing the Input for CNNs with the First-Order Scattering Transform
ECCV 2018
i-RevNet: Deep Invertible Networks
ICLR 2018
Building a Regular Decision Boundary With Deep Networks
CVPR 2017
Scaling the Scattering Transform: Deep Hybrid Networks
ICCV 2017
Deep Roto-Translation Scattering for Object Classification
CVPR 2015