Difference between revisions of "2018 VariationalAutoencodersforColla"

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* 7. Samuel R. Bowman, Luke Vilnis, Oriol Vinyals, Andrew M. Dai, Rafal Jozefowicz, and [[Samy Bengio]]. 2015. Generating Sentences from a Continuous Space. ArXiv Preprint ArXiv:1511.06349 (2015).
 
* 7. Samuel R. Bowman, Luke Vilnis, Oriol Vinyals, Andrew M. Dai, Rafal Jozefowicz, and [[Samy Bengio]]. 2015. Generating Sentences from a Continuous Space. ArXiv Preprint ArXiv:1511.06349 (2015).
 
* 8. Sotirios P. Chatzis, Panayiotis Christodoulou, Andreas S. Andreou, Recurrent Latent Variable Networks for Session-Based Recommendation, Proceedings of the 2nd Workshop on Deep Learning for Recommender Systems, August 27-27, 2017, Como, Italy [http://doi.acm.org/10.1145/3125486.3125493 doi:10.1145/3125486.3125493]
 
* 8. Sotirios P. Chatzis, Panayiotis Christodoulou, Andreas S. Andreou, Recurrent Latent Variable Networks for Session-Based Recommendation, Proceedings of the 2nd Workshop on Deep Learning for Recommender Systems, August 27-27, 2017, Como, Italy [http://doi.acm.org/10.1145/3125486.3125493 doi:10.1145/3125486.3125493]
* 9. Paul Covington, Jay Adams, Emre Sargin, Deep Neural Networks for YouTube Recommendations, Proceedings of the 10th ACM Conference on Recommender Systems, September 15-19, 2016, Boston, Massachusetts, USA [http://doi.acm.org/10.1145/2959100.2959190 doi:10.1145/2959100.2959190]
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* 9. [[Paul Covington]], Jay Adams, Emre Sargin, Deep Neural Networks for YouTube Recommendations, Proceedings of the 10th ACM Conference on Recommender Systems, September 15-19, 2016, Boston, Massachusetts, USA [http://doi.acm.org/10.1145/2959100.2959190 doi:10.1145/2959100.2959190]
 
* 10. Carl Doersch. 2016. Tutorial on Variational Autoencoders. ArXiv Preprint ArXiv:1606.05908 (2016).
 
* 10. Carl Doersch. 2016. Tutorial on Variational Autoencoders. ArXiv Preprint ArXiv:1606.05908 (2016).
 
* 11. Kostadin Georgiev, Preslav Nakov, A Non-IID Framework for Collaborative Filtering with Restricted Boltzmann Machines, Proceedings of the 30th International Conference on International Conference on Machine Learning, June 16-21, 2013, Atlanta, GA, USA
 
* 11. Kostadin Georgiev, Preslav Nakov, A Non-IID Framework for Collaborative Filtering with Restricted Boltzmann Machines, Proceedings of the 30th International Conference on International Conference on Machine Learning, June 16-21, 2013, Atlanta, GA, USA

Latest revision as of 22:33, 26 March 2020

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Abstract

We extend variational autoencoders (VAEs) to collaborative filtering for implicit feedback. This non-linear probabilistic model enables us to go beyond the limited modeling capacity of linear factor models which still largely dominate collaborative filtering research.We introduce a generative model with multinomial likelihood and use Bayesian inference for parameter estimation. Despite widespread use in language modeling and economics, the multinomial likelihood receives less attention in the recommender systems literature. We introduce a different regularization parameter for the learning objective, which proves to be crucial for achieving competitive performance. Remarkably, there is an efficient way to tune the parameter using annealing. The resulting model and learning algorithm has information-theoretic connections to maximum entropy discrimination and the information bottleneck principle. Empirically, we show that the proposed approach significantly outperforms several state-of-the-art baselines, including two recently-proposed neural network approaches, on several real-world datasets. We also provide extended experiments comparing the multinomial likelihood with other commonly used likelihood functions in the latent factor collaborative filtering literature and show favorable results. Finally, we identify the pros and cons of employing a principled Bayesian inference approach and characterize settings where it provides the most significant improvements.

References

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 AuthorvolumeDate ValuetitletypejournaltitleUrldoinoteyear
2018 VariationalAutoencodersforCollaDawen Liang
Rahul G. Krishnan
Matthew D. Hoffman
Tony Jebara
Variational Autoencoders for Collaborative Filtering10.1145/3178876.31861502018
AuthorDawen Liang +, Rahul G. Krishnan +, Matthew D. Hoffman + and Tony Jebara +
doi10.1145/3178876.3186150 +
titleVariational Autoencoders for Collaborative Filtering +
year2018 +