Autoencoder

Deep learning

Physics

Factorization

Collaborative filtering

Recommender system

Algorithm

Machine learning

Artificial intelligence

Eigenvalues and eigenvectors

MovieLens

Computer science

Quantum mechanics

Matrix decomposition

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.

AutoRec