TASK	DATASET	MODEL	METRIC NAME	METRIC VALUE	GLOBAL RANK	REMOVE
Recommendation Systems	MovieLens 10M	I-AutoRec	RMSE	0.782	# 10
Recommendation Systems	MovieLens 1M	I-AutoRec	RMSE	0.831	# 5

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AutoRec: Autoencoders Meet Collaborative Filtering

Proceedings of the 24th International Conference on World Wide Web 2015 · Suvash Sedhain, Aditya Krishna Menon, Scott Sanner, Lexing Xie ·

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

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