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Collaborative Filtering via Group-Structured Dictionary Learning

Szabo, Z; Póczos, A; Lőrincz, A; (2012) Collaborative Filtering via Group-Structured Dictionary Learning. In: (Proceedings) International Conference on Latent Variable Analysis and Signal Separation (LVA/ICA). (pp. 247 - 254). Springer-Verlag, Berlin Heidelberg Green open access

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Abstract

Structured sparse coding and the related structured dictionary learning problems are novel research areas in machine learning. In this paper we present a new application of structured dictionary learning for collaborative filtering based recommender systems. Our extensive numerical experiments demonstrate that the presented method outperforms its state-of-the-art competitors and has several advantages over approaches that do not put structured constraints on the dictionary elements.

Type: Proceedings paper
Title: Collaborative Filtering via Group-Structured Dictionary Learning
Event: International Conference on Latent Variable Analysis and Signal Separation (LVA/ICA)
Location: Tel-Aviv, Israel
Dates: 2012-03-12 - 2012-03-15
ISBN-13: 978-3-642-28550-9
Open access status: An open access version is available from UCL Discovery
DOI: 10.1007/978-3-642-28551-6_31
Publisher version: http://dx.doi.org/10.1007/978-3-642-28551-6_31
Language: English
Additional information: The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-28551-6_31
Keywords: collaborative filtering, structured dictionary learning
UCL classification: UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Gatsby Computational Neurosci Unit
URI: https://discovery.ucl.ac.uk/id/eprint/1433149
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