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Large-scale semi-supervised learning with online spectral graph sparsification

Daniele Calandriello 1 Alessandro Lazaric 1 Michal Valko 1
1 SEQUEL - Sequential Learning
Inria Lille - Nord Europe, CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189
Abstract : We introduce Sparse-HFS, a scalable algorithm that can compute solutions to SSL problems using only O(n polylog(n)) space and O(m polylog(n)) time.
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Submitted on : Thursday, June 22, 2017 - 11:56:25 AM
Last modification on : Thursday, January 20, 2022 - 4:16:39 PM
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Daniele Calandriello, Alessandro Lazaric, Michal Valko. Large-scale semi-supervised learning with online spectral graph sparsification. Resource-Efficient Machine Learning workshop at International Conference on Machine Learning, Jul 2015, Lille, France. ⟨hal-01544929⟩



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