Systems based on statistical and machine learning methods have been shown to be extremely effective and scalable for the analysis of large amount of textual data. However, in the r...
Graphical models have become the basic framework for topic based probabilistic modeling. Especially models with latent variables have proved to be effective in capturing hidden str...
We present a class of richly structured, undirected hidden variable models suitable for simultaneously modeling text along with other attributes encoded in different modalities. O...
Multiple realizations of continuous-valued time series from a stochastic process often contain systematic variations in rate and amplitude. To leverage the information contained i...
Jennifer Listgarten, Radford M. Neal, Sam T. Rowei...
Background: Computational prediction methods are currently used to identify genes in prokaryote genomes. However, identification of the correct translation initiation sites remain...
Yuko Makita, Michiel J. L. de Hoon, Antoine Danchi...