2 citations · 3 across the 3 of their papers we have counts for
4 papers
Learning from Multiple Sources for Data-to-Text and Text-to-Data
Song Duong, Alberto Lumbreras, Mike Gartrell +1
Data-to-text (D2T) and text-to-data (T2D) are dual tasks that convert structured data, such as graphs or tables into fluent text, and vice versa. These tasks are usually handled se…
Non-parametric clustering over user features and latent behavioral functions with dual-view mixture models
Alberto Lumbreras, Julien Velcin, Marie Guégan +1
We present a dual-view mixture model to cluster users based on their features and latent behavioral functions. Every component of the mixture model represents a probability density…
Bayesian Mean-parameterized Nonnegative Binary Matrix Factorization
Alberto Lumbreras, Louis Filstroff, Cédric Févotte
Binary data matrices can represent many types of data such as social networks, votes, or gene expression. In some cases, the analysis of binary matrices can be tackled with nonnega…
Closed-form Marginal Likelihood in Gamma-Poisson Matrix Factorization
Louis Filstroff, Alberto Lumbreras, Cédric Févotte
We present novel understandings of the Gamma-Poisson (GaP) model, a probabilistic matrix factorization model for count data. We show that GaP can be rewritten free of the score/act…