Nonparametric methods are widely applicable to statistical learning problems, since they rely on a few modeling assumptions. In this context, the fresh look advocated here permeat...
The hierarchical Dirichlet process hidden Markov model (HDP-HMM) is a flexible, nonparametric model which allows state spaces of unknown size to be learned from data. We demonstra...
Emily B. Fox, Erik B. Sudderth, Michael I. Jordan,...
The recent development of Sequential Monte Carlo methods (also called particle filters) has enabled the definition of efficient algorithms for tracking applications in image sequen...
On-line analytical processing (OLAP) requires e cient processing of complex decision support queries over very large databases. It is well accepted that pre-computed data cubes ca...
David Wai-Lok Cheung, Bo Zhou, Ben Kao, Hongjun Lu...
Online communities like Flickr, del.icio.us and YouTube have established themselves as very popular and powerful services for publishing and searching contents, but also for ident...
Tom Crecelius, Mouna Kacimi, Sebastian Michel, Tho...