Semi-supervised Spectral Clustering - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2018

Semi-supervised Spectral Clustering

Résumé

In this article, we propose a semi-supervised version of spectral clustering, a widespread graph-based unsupervised learning method. The semi-supervised spectral clustering has the advantage of producing consistent classification of data with sufficiently large number of labelled or unlabelled data, unlike classical graph-based semi-supervised methods which are only consistent on labelled data. Theoretical arguments are provided to support the proposition of this novel approach, as well as empirical evidence to confirm the theoretical claims and demonstrate its superiority over other graph-based semi-supervised methods.
Fichier principal
Vignette du fichier
SSL_clustering(1).pdf (80.25 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-01982268 , version 1 (15-01-2019)

Identifiants

Citer

Xiaoyi Mai, Romain Couillet. Semi-supervised Spectral Clustering. ACSSC 2018 - 52nd Annual Asilomar Conference on Signals, Systems, and Computers, Oct 2018, Pacific Grove, United States. ⟨10.1109/acssc.2018.8645278⟩. ⟨hal-01982268⟩
85 Consultations
595 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More