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Communication Dans Un Congrès Année : 2019

ParKerC: Toolbox for Parallel Kernel Clustering Methods

Résumé

A large variety of fields such as biology, information retrieval, image segmentation needs unsupervised methods able to gather data without a priori information on shapes or locality. By investigating a parallel strategy based on overlapping domain decomposition, we present a toolbox which is a parallel implementation of two fully unsupervised kernel methods respectively based on density-based properties and spectral properties in order to treat large data sets in fields of pattern recognition.
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Dates et versions

hal-03003819 , version 1 (17-11-2020)

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Sandrine Mouysset, Ronan Guivarch. ParKerC: Toolbox for Parallel Kernel Clustering Methods. 10th International Conference on Pattern Recognition Systems - ICPRS 2019, Jul 2019, Tours, France. ⟨10.1049/cp.2019.0253⟩. ⟨hal-03003819⟩
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