Oyallon, Edouard

31 publications

NeurIPS 2025 ACCO: Accumulate While You Communicate for Communication-Overlapped Sharded LLM Training Adel Nabli, Louis Fournier, Pierre Erbacher, Louis Serrano, Eugene Belilovsky, Edouard Oyallon

ICML 2025 DISCO: Learning to DISCover an Evolution Operator for Multi-Physics-Agnostic Prediction Rudy Morel, Jiequn Han, Edouard Oyallon

JMLR 2025 Decentralized Asynchronous Optimization with DADAO Allows Decoupling and Acceleration Adel Nabli, Edouard Oyallon

ICLR 2025 PETRA: Parallel End-to-End Training with Reversible Architectures Stephane Rivaud, Louis Fournier, Thomas Pumir, Eugene Belilovsky, Michael Eickenberg, Edouard Oyallon

NeurIPSW 2024 $\mu$LO: Compute-Efficient Meta-Generalization of Learned Optimizers Benjamin Thérien, Charles-Étienne Joseph, Boris Knyazev, Edouard Oyallon, Irina Rish, Eugene Belilovsky

NeurIPSW 2024 ACCO: Accumulate While You Communicate, Hiding Communications in Distributed LLM Training Adel Nabli, Louis Fournier, Pierre Erbacher, Louis Serrano, Eugene Belilovsky, Edouard Oyallon

NeurIPSW 2024 Cyclic Data Parallelism for Efficient Parallelism of Deep Neural Networks Louis Fournier, Edouard Oyallon

NeurIPSW 2024 WASH: Train Your Ensemble with Communication-Efficient Weight Shuffling, Then Average Louis Fournier, Adel Nabli, Masih Aminbeidokhti, Marco Pedersoli, Eugene Belilovsky, Edouard Oyallon

NeurIPS 2023 $\textbf{A}^2\textbf{CiD}^2$: Accelerating Asynchronous Communication in Decentralized Deep Learning Adel Nabli, Eugene Belilovsky, Edouard Oyallon

ICML 2023 Can Forward Gradient Match Backpropagation? Louis Fournier, Stephane Rivaud, Eugene Belilovsky, Michael Eickenberg, Edouard Oyallon

ICML 2023 DADAO: Decoupled Accelerated Decentralized Asynchronous Optimization Adel Nabli, Edouard Oyallon

TMLR 2023 Gradient Masked Averaging for Federated Learning Irene Tenison, Sai Aravind Sreeramadas, Vaikkunth Mugunthan, Edouard Oyallon, Irina Rish, Eugene Belilovsky

NeurIPS 2023 Guiding the Last Layer in Federated Learning with Pre-Trained Models Gwen Legate, Nicolas Bernier, Lucas Page-Caccia, Edouard Oyallon, Eugene Belilovsky

ICMLW 2023 Guiding the Last Layer in Federated Learning with Pre-Trained Models Gwen Legate, Nicolas Bernier, Lucas Caccia, Edouard Oyallon, Eugene Belilovsky

NeurIPSW 2023 Modeling String Entries for Tabular Data Prediction: Do We Need Big Large Language Models? Leo Grinsztajn, Myung Jun Kim, Edouard Oyallon, Gael Varoquaux

ICMLW 2023 Preventing Dimensional Collapse in Contrastive Local Learning with Subsampling Louis Fournier, Adeetya Patel, Michael Eickenberg, Edouard Oyallon, Eugene Belilovsky

NeurIPS 2022 On Non-Linear Operators for Geometric Deep Learning Grégoire Sergeant-Perthuis, Jakob Maier, Joan Bruna, Edouard Oyallon

NeurIPS 2022 Why Do Tree-Based Models Still Outperform Deep Learning on Typical Tabular Data? Leo Grinsztajn, Edouard Oyallon, Gael Varoquaux

ICLRW 2021 Low-Rank Projections of GCNs Laplacian Nathan Grinsztajn, Philippe Preux, Edouard Oyallon

ICLR 2021 The Unreasonable Effectiveness of Patches in Deep Convolutional Kernels Methods Louis Thiry, Michael Arbel, Eugene Belilovsky, Edouard Oyallon

ICML 2020 Decoupled Greedy Learning of CNNs Eugene Belilovsky, Michael Eickenberg, Edouard Oyallon

ICML 2020 Interferometric Graph Transform: A Deep Unsupervised Graph Representation Edouard Oyallon

MLOSS 2020 Kymatio: Scattering Transforms in Python Mathieu Andreux, Tomás Angles, Georgios Exarchakis, Roberto Leonarduzzi, Gaspar Rochette, Louis Thiry, John Zarka, Stéphane Mallat, Joakim Andén, Eugene Belilovsky, Joan Bruna, Vincent Lostanlen, Muawiz Chaudhary, Matthew J. Hirn, Edouard Oyallon, Sixin Zhang, Carmine Cella, Michael Eickenberg

ICML 2019 Greedy Layerwise Learning Can Scale to ImageNet Eugene Belilovsky, Michael Eickenberg, Edouard Oyallon

NeurIPS 2019 On Lazy Training in Differentiable Programming Lénaïc Chizat, Edouard Oyallon, Francis Bach

ECCV 2018 Compressing the Input for CNNs with the First-Order Scattering Transform Edouard Oyallon, Eugene Belilovsky, Sergey Zagoruyko, Michal Valko

ICLR 2018 I-RevNet: Deep Invertible Networks Jörn-Henrik Jacobsen, Arnold W.M. Smeulders, Edouard Oyallon

CVPR 2017 Building a Regular Decision Boundary with Deep Networks Edouard Oyallon

ICCV 2017 Scaling the Scattering Transform: Deep Hybrid Networks Edouard Oyallon, Eugene Belilovsky, Sergey Zagoruyko

CVPR 2015 Deep Roto-Translation Scattering for Object Classification Edouard Oyallon, Stephane Mallat

ICLR 2014 Generic Deep Networks with Wavelet Scattering Edouard Oyallon, Stéphane Mallat, Laurent Sifre