Coupled Compound Poisson Factorization

no code implementations • 9 Jan 2017 • Mehmet E. Basbug, Barbara E. Engelhardt

We present a general framework, the coupled compound Poisson factorization (CCPF), to capture the missing-data mechanism in extremely sparse data sets by coupling a hierarchical Poisson factorization with an arbitrary data-generating model.

Clustering Variational Inference

Dynamic Collaborative Filtering with Compound Poisson Factorization

no code implementations • 17 Aug 2016 • Ghassen Jerfel, Mehmet E. Basbug, Barbara E. Engelhardt

Model-based collaborative filtering analyzes user-item interactions to infer latent factors that represent user preferences and item characteristics in order to predict future interactions.

Collaborative Filtering Variational Inference

Hierarchical Compound Poisson Factorization

no code implementations • 13 Apr 2016 • Mehmet E. Basbug, Barbara E. Engelhardt

Here, we introduce hierarchical compound Poisson factorization (HCPF) that has the favorable Gamma-Poisson structure and scalability of HPF to high-dimensional extremely sparse matrices.

Collaborative Filtering Recommendation Systems