We describe the use of a hierarchical topic model for automatically identifying syntactic and lexical patterns that explicitly state ontological relations. We leverage distant sup...
In this paper we introduce a probabilistic framework to exploit hierarchy, structure sharing and duration information for topic transition detection in videos. Our probabilistic d...
Dinh Q. Phung, Thi V. Duong, Svetha Venkatesh, Hun...
Abstract. We propose a novel probabilistic method, based on latent variable models, for unsupervised topographic visualisation of dynamically evolving, coherent textual information...
In this work we address the problem of modeling varying time duration sequences for large-scale human routine discovery from cellphone sensor data using a multi-level approach to p...
Abstract--With the increased presence of digital imaging devices, there also came an explosion in the amount of multimedia content available online. Users have transformed from pas...