Training Deep AutoEncoders for Collaborative Filtering

5 Aug 2017 Oleksii Kuchaiev Boris Ginsburg

This paper proposes a novel model for the rating prediction task in recommender systems which significantly outperforms previous state-of-the art models on a time-split Netflix data set. Our model is based on deep autoencoder with 6 layers and is trained end-to-end without any layer-wise pre-training... (read more)

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