Document clustering techniques mostly depend on models that impose explicit and/or implicit priori assumptions as to the number, size, disjunction characteristics of clusters, and/...
We develop hierarchical, probabilistic models for objects, the parts composing them, and the visual scenes surrounding them. Our approach couples topic models originally developed...
Erik B. Sudderth, Antonio Torralba, William T. Fre...
There are currently a large number of ‘‘orphan’’ G-protein-coupled receptors (GPCRs) whose endogenous ligands (peptide hormones) are unknown. Identification of these pepti...
The features of the emerging modeling languages for system design allow designers to build models of almost any kind of heterogeneous hardware-software systems, including Real Tim...
Marcello Mura, Luis Gabriel Murillo, Mauro Prevost...
In this paper, we develop multilingual supervised latent Dirichlet allocation (MLSLDA), a probabilistic generative model that allows insights gleaned from one language's data...