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