Weimer, Markus ; Karatzoglou, Alexandros ; Smola, Alex
Hrsg.: Daelemans, Walter ; Goethals, Bart ; Morik, Katharina (2008)
Improving Maximum Margin Matrix Factorization <b> (best machine learning paper award)</b>.
Konferenzveröffentlichung, Bibliographie
Kurzbeschreibung (Abstract)
Collaborative filtering is a popular method for personalizing product recommendations. Maximum Margin Matrix Factorization (MMMF) has been proposed as one successful learning approach to this task and has been recently extended to structured ranking losses. In this paper we discuss a number of extensions to MMMF by introducing offset terms, item dependent regularization and a graph kernel on the recommender graph. We show equivalence between graph kernels and the recent MMMF extensions by Mnih and Salakhutdinov (Advances in Neural Information Processing Systems 20, 2008). Experimental evaluation of the introduced extensions show improved performance over the original MMMF formulation.
| Typ des Eintrags: | Konferenzveröffentlichung |
|---|---|
| Erschienen: | 2008 |
| Herausgeber: | Daelemans, Walter ; Goethals, Bart ; Morik, Katharina |
| Autor(en): | Weimer, Markus ; Karatzoglou, Alexandros ; Smola, Alex |
| Art des Eintrags: | Bibliographie |
| Titel: | Improving Maximum Margin Matrix Factorization <b> (best machine learning paper award)</b> |
| Sprache: | Deutsch |
| Publikationsjahr: | 2008 |
| Verlag: | Springer |
| Buchtitel: | Machine Learning and Knowledge Discovery in Databases |
| Reihe: | LNAI |
| Band einer Reihe: | 5211 |
| Kurzbeschreibung (Abstract): | Collaborative filtering is a popular method for personalizing product recommendations. Maximum Margin Matrix Factorization (MMMF) has been proposed as one successful learning approach to this task and has been recently extended to structured ranking losses. In this paper we discuss a number of extensions to MMMF by introducing offset terms, item dependent regularization and a graph kernel on the recommender graph. We show equivalence between graph kernels and the recent MMMF extensions by Mnih and Salakhutdinov (Advances in Neural Information Processing Systems 20, 2008). Experimental evaluation of the introduced extensions show improved performance over the original MMMF formulation. |
| ID-Nummer: | TUD-CS-2008-1210 |
| Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik > Telekooperation 20 Fachbereich Informatik |
| Hinterlegungsdatum: | 31 Dez 2016 12:59 |
| Letzte Änderung: | 15 Mai 2018 12:01 |
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