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3IA Côte d'Azur - Interdisciplinary Institute for Artificial Intelligence
3IA Côte d'Azur est l'un des quatre "Instituts interdisciplinaires d'intelligence artificielle" créés en France en 2019. Son ambition est de créer un écosystème innovant et influent au niveau local, national et international. L'institut 3IA Côte d'Azur est piloté par Université Côte d'Azur en partenariat avec les grands partenaires de l'enseignement supérieur et de la recherche de la région niçoise et de Sophia Antipolis : CNRS, Inria, INSERM, EURECOM, SKEMA Business School. L'institut 3IA Côte d'Azur est également soutenu par l'ECA, le CHU de Nice, le CSTB, le CNES, l'Institut Data ScienceTech et l'INRAE. Le projet a également obtenu le soutien de plus de 62 entreprises et start-ups.
Derniers dépôts
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Riccardo Taiello, Melek Önen, Clémentine Gritti, Marco Lorenzi. Let Them Drop: Scalable and Efficient Federated Learning Solutions Agnostic to Stragglers. ARES 2024 - 19th International Conference on Availability, Reliability and Security, Jul 2024, Vienna, Austria. pp.1-12, ⟨10.1145/3664476.3664488⟩. ⟨hal-04742784⟩
Documents en texte intégral
699
Notices
308
Statistiques par discipline
Mots clés
SPARQL
Electronic medical record
Computing methodologies
Correlation matrices
Coxeter triangulation
CNN
Semantic segmentation
Federated Learning
Knowledge graphs
Super-resolution
FPGA
Diffusion strategy
ECG
Federated learning
Web of Things
Unsupervised learning
Semantic Web
Semantic web
Differential privacy
Change point detection
Visualization
Autonomous vehicles
Diffusion MRI
Deep Learning
Isomanifolds
Macroscopic traffic flow models
Echocardiography
MRI
Argument mining
Fluorescence microscopy
Domain adaptation
Electrophysiology
Biomarkers
COVID-19
Linked data
Graph signal processing
Atrial fibrillation
Artificial Intelligence
Image segmentation
Spiking neural networks
Persistent homology
Neural networks
Cable-driven parallel robot
Linked Data
53B20
Excursion sets
Optimization
Knowledge graph
Convolutional Neural Networks
Dimensionality reduction
Information Extraction
Atrial Fibrillation
Grammatical Evolution
Data augmentation
Deep learning
Distributed optimization
Autoencoder
Contrastive learning
Computational Topology
Consensus
Graph neural networks
Explainable AI
Alzheimer's disease
Apprentissage profond
Hyperspectral data
Dense labeling
Argument Mining
Multi-Agent Systems
Hyperbolic systems of conservation laws
Ontology Learning
Brain-inspired computing
Geometric graphs
Privacy
Image fusion
Sparsity
Computer vision
Topological Data Analysis
Uncertainty
NLP Natural Language Processing
Convergence analysis
Clinical trials
Segmentation
Electrocardiogram
Convolutional neural networks
Extracellular matrix
OPAL-Meso
Spiking Neural Networks
Artificial intelligence
Co-clustering
Latent block model
Predictive model
Anomaly detection
Embedded Systems
Convolutional neural network
Healthcare
Arguments
Machine learning
Clustering
Extreme value theory
RDF