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Inria, the French national research institute for the digital sciences | Saint Martin, Midi Pyrenees | France | 14 days ago
Conference on High Performance Computing, Data, and Analytics (HiPC 2017). https://legion.stanford.edu/pdfs/hipc2017.pdf Visibility Algorithms for Dynamic Dependence Analysis and Distributed Coherence. Michael
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? • comment se comportent-elles face à des données hétérogènes (par exemple, personnalisées ou dont les distributions statistiques ne sont pas identiques dans tous les ensembles de données), ce qui est fréquent
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Inria, the French national research institute for the digital sciences | Saint Martin, Midi Pyrenees | France | 14 days ago
follows a phased algorithm: 1) generate an initial training set by uniformly sampling input points 2) (re)train the model on the trainng set 3) use feedback from the model’s performance to generate/augment
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Laboratoire National de Métrologie et d'Essais - LNE | Paris 15, le de France | France | about 1 month ago
according to established rules, the second approach can pave the way to a respective verification service provided by European NMIs. Reference data generation and robust point cloud partitioning algorithms
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Inria, the French national research institute for the digital sciences | Saint Martin, Midi Pyrenees | France | about 1 month ago
to compare base approaches (no active learning) with different state-of-the-art active learning algorithms including our solutions; Participate to the redaction of a publication exposing the methodologies and
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the values are drawn independently from known distributions. These results have been widely applied in areas such as auction theory, resource allocation, and stochastic optimization. The interdependent value
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, the post-doctoral fellow will consider designing distributed learning algorithms for streaming manifold-valued data. Experiments will be carried out on urban, coastal, and underwater DAS data. The novelty
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frameworks, as they impose minimal, if any, assumptions about the underlying data distribution, making them more effective for detecting a wide range of changes. The CPD algorithms will be designed
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. The monitoring of telecommunications and energy production and distribution networks are characteristic examples of such time-critical applications. The project aims to propose unsupervised online CPD algorithms
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suitable data models [CSC+23]. Objectives As far as the design of efficient numerical algorithms in an off-the-grid setting is concerned, the problem is challenging, since the optimization is defined in