Publications

Affichage de 71 à 80 sur 5385


  • Ouvrages

Conférence Nationale d’Intelligence Artificielle Année 2024

Emmanuel Adam, Thomas Guyet, Benoit Le Blanc, Dominique Longin, Nadia Abchiche-Mimouni, Ghislain Atemezing, Nathalie Aussenac-Gilles, Jean-Guy Mailly, Catherine Roussey, François Schwarzentruber, Anaelle Wilczynski, Haïfa Zargayouna

Activités de l'AFIA du 1er août 2022 au 31 juillet 2024, et sélection de papiers issus de PFIA 2024

Association Française pour l'Intelligence Artificielle, 2024. ⟨hal-04748891⟩

  • Article dans une revue

Controllability of heterogeneous multi-agent systems via cooperative output regulation

Jun Jiang, Yiwen Chen, Othman Lakhal, Rochdi Merzouki

Journal of The Franklin Institute, 2024, 361 (15), pp.107133. ⟨10.1016/j.jfranklin.2024.107133⟩. ⟨hal-04687211⟩

  • Communication dans un congrès

An Efficient Decentralized Fine-grained Access Control for IoT Ecosystems over NDN

Ferhat Mecerhed, Youcef Imine, Antoine Gallais, Stefan Fischer, Mohamed Ahmed Hail

2024 International Conference on Software, Telecommunications and Computer Networks (SoftCOM), Sep 2024, Split, France. pp.1-6, ⟨10.23919/SoftCOM62040.2024.10721767⟩. ⟨hal-05031066⟩

  • Communication dans un congrès

A Literature Review and Taxonomy Proposal of Industrial Symbiosis Practices

Soukaina Benchari, Cecilia Daquin, Emmanuelle Grislin-Le Strugeon, Yves Sallez

In response to the environmental repercussions of the linear economy model, the circular economy has emerged, aiming to reduce environmental impact while balancing economic and social aspects. Industrial ecology is a pillar of cir- cular economy, facilitating collaboration among local industries…

Int. Workshop on Service-Oriented, Holonic and Multi-Agent Manufacturing Systems for Industry of the Future (SOHOMA), Sep 2024, Augsburg, Germany. ⟨hal-04991038⟩

  • Communication dans un congrès

Accelerated NAS via pretrained ensembles and multi-fidelity Bayesian Optimization

Houssem Ouertatani, Cristian Maxim, Smail Niar, El-Ghazali Talbi

Bayesian optimization (BO) is a black-box search method particularly valued for its sample efficiency. It is especially effective when evaluations are very costly, such as in hyperparameter optimization or Neural Architecture Search (NAS). In this work, we design a fast NAS method based on BO.…

33rd International Conference on Artificial Neural Networks (ICANN), Sep 2024, Lugano, Switzerland. ⟨10.1007/978-3-031-72332-2_17⟩. ⟨hal-04611343⟩

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