Ayed, Fadhel

11 publications

TMLR 2025 Over-Parameterised Shallow Neural Networks with Asymmetrical Node Scaling: Global Convergence Guarantees and Feature Learning Francois Caron, Fadhel Ayed, Paul Jung, Hoil Lee, Juho Lee, Hongseok Yang

NeurIPSW 2024 Pay Attention to What Matters Pedro Luiz Silva, Fadhel Ayed, Antonio De Domenico, Ali Maatouk

TMLR 2023 Data Pruning and Neural Scaling Laws: Fundamental Limitations of Score-Based Algorithms Fadhel Ayed, Soufiane Hayou

JMLR 2023 Deep Neural Networks with Dependent Weights: Gaussian Process Mixture Limit, Heavy Tails, Sparsity and Compressibility Hoil Lee, Fadhel Ayed, Paul Jung, Juho Lee, Hongseok Yang, Francois Caron

NeurIPSW 2023 Deep Neural Networks with Dependent Weights: \\Gaussian Process Mixture Limit, Heavy Tails, Sparsity and Compressibility Hoil Lee, Fadhel Ayed, Paul Jung, Juho Lee, Hongseok Yang, Francois Caron

NeurIPSW 2023 FlexTrain: A Dynamic Training Framework for Heterogeneous Devices Environments Mert Unsal, Ali Maatouk, Antonio De Domenico, Nicola Piovesan, Fadhel Ayed

NeurIPSW 2023 Over-Parameterised Shallow Neural Networks with Asymmetrical Node Scaling: \\ Global Convergence Guarantees and Feature Learning Fadhel Ayed, Francois Caron, Paul Jung, Juho Lee, Hoil Lee, Hongseok Yang

NeurIPSW 2022 The Curse of (non)convexity: The Case of an Optimization-Inspired Data Pruning Algorithm Fadhel Ayed, Soufiane Hayou

JMLR 2021 Consistent Estimation of Small Masses in Feature Sampling Fadhel Ayed, Marco Battiston, Federico Camerlenghi, Stefano Favaro

NeurIPS 2021 Regularization in ResNet with Stochastic Depth Soufiane Hayou, Fadhel Ayed

ICML 2019 Beyond the Chinese Restaurant and Pitman-Yor Processes: Statistical Models with Double Power-Law Behavior Fadhel Ayed, Juho Lee, Francois Caron