Huy V. Vo, Vasil Khalidov, Timothée Darcet, Théo Moutakanni, Nikita Smetanin, Marc Szafraniec, Hugo Touvron, Camille Couprie, Maxime Oquab, Armand Joulin, Hervé Jégou, Patrick Labatut, Piotr ...
At the heart of Apache Spark is the concept of the Resilient Distributed Dataset (RDD), a programming abstraction that represents an immutable collection of objects that can be split across a ...
Clustering is usually the first exploratory analysis step in empirical data. When the data set comprises graphs, the most common approaches focus on clustering its vertices. In this work, we are ...
1 Department of Communication Science and Engineering, Nelson Mandela Institution of Science and Technology, Arusha, Tanzania. 2 School for Information Sciences, Center for Information and Systems, ...
We release paper and code for SwAV, our new self-supervised method. SwAV pushes self-supervised learning to only 1.2% away from supervised learning on ImageNet with a ResNet-50! It combines online ...
Fiber clustering methods are typically used in brain research to study the organization of white matter bundles from large diffusion MRI tractography datasets. These methods enable exploratory bundle ...
CLARANS (Clustering Large Applications based on RANdomized Search) is a Data Mining algorithm designed to cluster spatial data. CLARANS is a clustering algorithm that focuses on spatial data mining, ...
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