Reviews: Gamma-Poisson Dynamic Matrix Factorization Embedded with Metadata Influence

Summary: The authors develop a Gamma-Poisson factorization model that includes metadata and models user preferences and item attractiveness in a dynamic context. They develop a variational inference algorithm and demonstrate that their approach outperforms other methods on five data sets. Quality: The technical quality of this work appears to be sound. For evaluation, the metrics used are in line with the way these systems are actually deployed (e.g., rank-based instead of just RMSE of the ratings). I think the authors sell Gaussian MF a little short.