When building an application that requires object class recognition, having enough data to learn from is critical for good performance, and can easily determine the success or fai...
This paper presents a novel approach to the unsupervised learning of syntactic analyses of natural language text. Most previous work has focused on maximizing likelihood according...
Many practitioners who use EM and related algorithms complain that they are sometimes slow. When does this happen, and what can be done about it? In this paper, we study the gener...
Ruslan Salakhutdinov, Sam T. Roweis, Zoubin Ghahra...
Markov statistical methods may make it possible to develop an unsupervised learning process that can automatically identify genomic structure in prokaryotes in a comprehensive way...
We take a multivariate view of digital search trees by studying the number of nodes of different types that may coexist in a bucket digital search tree as it grows under an arbitr...
Friedrich Hubalek, Hsien-Kuei Hwang, William Lew, ...