Quantum mechanics

Machine learning

Autoencoder

Deep learning

Computer science

Matrix decomposition

Recommender system

Physics

Artificial intelligence

Algorithm

Eigenvalues and eigenvectors

MovieLens

Factorization

Collaborative filtering

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