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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.
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Yehuda Koren. 2009 · 2009
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Matrix factorization techniques for recommender systems
Yehuda Koren, Robert Bell, and Chris Volinsky. 2009 · 2009
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Collaborative filtering with temporal dynamics
Yehuda Koren. 2010 · 2010
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Context-aware recommender systems
Gediminas Adomavicius and Alexander Tuzhilin. 2011 · 2011
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Francesco Ricci, Lior Rokach, and Bracha Shapira. 2011 · 2011
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Fast and accurate deep network learning by exponential linear units (elus)
Djork-Arné Clevert, Thomas Unterthiner, and Sepp Hochreiter. 2015 · 2015
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Autorec: Autoencoders meet collaborative filtering. In Proceedings of the 24th International Conference on World Wide Web
Suvash Sedhain, Aditya Krishna Menon, Scott Sanner, and Lexing Xie. 2015 · 2015
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Collaborative filtering with stacked denoising autoencoders and sparse inputs. In NIPS workshop on machine learning for eCommerce
Florian Strub and Jérémie Mary. 2015 · 2015
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Empirical evaluation of rectified activations in convolutional network
Bing Xu, Naiyan Wang, Tianqi Chen, and Mu Li. 2015 · 2015
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Neural collaborative filtering. In Proceedings of the 26th International Conference on World Wide Web
Xiangnan He, Lizi Liao, Hanwang Zhang, Liqiang Nie, Xia Hu, and Tat-Seng Chua. 2017 · 2017
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Deep learning
Yann LeCun, Yoshua Bengio, and Geoffrey Hinton. 2015 · 2015
Cited alongside, same era.
Günter Klambauer, Thomas Unterthiner, Andreas Mayr, and Sepp Hochreiter. 2017 · 2017
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Recurrent Recommender Networks. In Proceedings of the Tenth ACM International Conference on Web Search and Data Mining
Chao-Yuan Wu, Amr Ahmed, Alex Beutel, Alexander J. Smola, and How Jing. 2017 · 2017
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