Communication dans un congrès
Apprentissage
Affichage des résultats 1 à 12 sur 122 au total
Apprentissage : 1 à 12 sur 122 au total
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Communication dans un congrès
Jose Lucas de Melo Costa, Fabrice Popineau, Bich-Liên Doan, Arpad Rimmel, Fabrice Daniel. Leveraging Self-Supervised Learning for Fraud Detection in Tabular Data. 19th Financial Risks International Forum, Institut Louis Bachelier, Mar 2026, Paris, France. ⟨hal-05672093⟩
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Pré-publication, Document de travail
Pierre Wolinski, Guillaume Charpiat, Yann Ollivier. Asymmetrical Scaling Layers for Stable Network Pruning. 2020. ⟨hal-05524815⟩
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Thèse
Yeabsira Ashengo. Intelligent Task Offloading and Resource Allocation with Multi-access Edge Computing Servers using 5G for Tactile Internet. Mobile Computing. Université Paris-Saclay, 2025. English. ⟨NNT : 2025UPASG086⟩. ⟨tel-05525673⟩
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Pré-publication, Document de travail
Lucas Ondel Yang, Tina Raissi, Martin Kocour, Pablo Riera, Caio Corro. Fast and General Automatic Differentiation for Finite-State Methods. 2026. ⟨hal-05500843⟩
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Communication dans un congrès
Ludovic Arnold, Sébastien Rebecchi, Sylvain Chevallier, Hélène Paugam-Moisy. An Introduction to Deep Learning. European Symposium on Artificial Neural Networks (ESANN), Apr 2011, Bruges, Belgium. ⟨hal-01352061⟩
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Communication dans un congrès
Onofrio Semeraro, Michele Alessandro Bucci, Lionel Mathelin, Luigi Marra, Amine Saibi. From robotics to fluid dynamics: opportunities and pitfalls of Reinforcement Learning in flow control. iTi Workshop on Structure and control of wall-bounded turbulent flows, Jul 2025, Bertinoro, Italy. ⟨hal-05379587⟩
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Article dans une revue
Amine Saibi, Lionel Mathelin, Onofrio Semeraro. A Multistep Reinforcement Learning Control of Shear Flows in Minimal Input–Output Plants Under Large Time-delays. Flow, Turbulence and Combustion, 2025, 115 (3), pp.1379-1402. ⟨10.1007/s10494-025-00697-w⟩. ⟨hal-05379450⟩
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Article dans une revue
Michele Quattromini, Michele Alessandro Bucci, Stefania Cherubini, Onofrio Semeraro. Mean flow data assimilation using physics-constrained graph neural networks. Data-Centric Engineering, 2025, 6, pp.e48. ⟨10.1017/dce.2025.10022⟩. ⟨hal-05379441⟩
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Communication dans un congrès
Eliott Pradeleix, Rémy Hosseinkhan-Boucher, Alena Shilova, Onofrio Semeraro, Lionel Mathelin. Learning Meets Differential Equations: From Theory to Applications Learning non-Markovian Dynamical Systems with Signature-based Encoders. ML-DE 2025 - 2nd Workshop on "Machine Learning Meets Differential Equations: From Theory to Applications",, Oct 2025, Bologna, Italy. pp.1-25. ⟨hal-05379481⟩
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Article dans une revue
Mathurin Videau, Alessandro Leite, Marc Schoenauer, Olivier Teytaud. Mixture of Experts for Image Classification: What's the Sweet Spot?. Transactions on Machine Learning Research Journal, 2025. ⟨hal-05329451⟩
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Pré-publication, Document de travail
Antoine Szatkownik, Aurélien Decelle, Beatriz Seoane, Nicolas Béreux, Léo Planche, et al.. PRIVET: Privacy Metric Based On Extreme Value Theory. 2025. ⟨hal-05326013⟩