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Poisson factorization is a probabilistic model of users and items for recommendation systems, where the so-called implicit consumer data is modeled by a factorized Poisson distribution.
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Bayesian Nonparametric Poisson Factorization for Recommendation Systems.. In AISTATS
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Content-based recommendations with poisson factorization. In Advances in Neural Information Processing Systems
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Recurrent marked temporal point processes: Embedding event history to vector. In Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
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Coevolutionary latent feature processes for continuous-time user-item interactions. In Advances in Neural Information Processing Systems
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Time-sensitive recommendation from recurrent user activities. In Advances in Neural Information Processing Systems
Nan Du, Yichen Wang, Niao He, Jimeng Sun, and Le Song. 2015 · 2015
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Scalable Recommendation with Hierarchical Poisson Factorization.. In UAI
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Correlated Cascades: Compete or Cooperate. In Proceedings of the 31st AAAI Conference on Artificial Intelligence
Ali Zarezade, Ali Khodadadi, Mehrdad Farajtabar, Hamid R Rabiee, and Hongyuan Zha. 2016b
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Ali Zarezade, Sina Jafarzadeh, and Hamid R Rabiee. 2016a · 2016
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Neural Survival Recommender. In Proceedings of the Tenth ACM International Conference on Web Search and Data Mining
How Jing and Alexander J Smola. 2017 · 2017
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Continuous-Time User Modeling in the Presence of Badges: A Probabilistic Approach
Ali Khodadadi, Seyed Abbas Hosseini, Erfan Tavakoli, and Hamid R Rabiee. 2017 · 2017
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