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Graph-based semi-supervised learning /

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While labeled data is expensive to prepare, ever increasing amounts of unlabeled data is becoming widely available. In order to adapt to this phenomenon, several semi-supervised learning (SSL) algorithms, which learn from labeled as well as unlabeled data, have been developed. In a separate line of...

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Dettagli Bibliografici
Autori principali:	Subramanya, Amarnag (Autore), Talukdar, Partha Pratim (Autore)
Natura:	eBook
Lingua:	English
Pubblicazione:	San Rafael, California (1537 Fourth Street, San Rafael, CA 94901 USA) : Morgan & Claypool, 2014.
Serie:	Synthesis digital library of engineering and computer science. Synthesis lectures on artificial intelligence and machine learning ; # 29.
Soggetti:	Machine learning > Graphic methods. Supervised learning (Machine learning) graph Laplacian graph-based learning graph-based semi-supervised learning inductive learning label propagation manifold learning nonparametric learning scalable machine learning semi-supervised learning transductive learning
Accesso online:	Abstract with links to full text

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