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AutoRec: Autoencoders Meet Collaborative Filtering

Sedhain, Suvash; Menon, Aditya; Sanner, Scott; Xie, Lexing


This paper proposes AutoRec, a novel autoencoder framework for collaborative filtering (CF). Empirically, AutoRec's compact and efficiently trainable model outperforms state-of-the-art CF techniques (biased matrix factorization, RBM-CF and LLORMA) on the Movielens and Netflix datasets

CollectionsANU Research Publications
Date published: 2015
Type: Conference paper
Source: AutoRec: Autoencoders Meet Collaborative Filtering
DOI: 10.1145/2740908.2742726


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