We present a directed Markov random field (MRF) model that combines n-gram models, probabilistic context free grammars (PCFGs) and probabilistic latent semantic analysis (PLSA) fo...
Shaojun Wang, Shaomin Wang, Russell Greiner, Dale ...
Hidden Markov models (HMMs) are a powerful probabilistic tool for modeling sequential data, and have been applied with success to many text-related tasks, such as part-of-speech t...
Andrew McCallum, Dayne Freitag, Fernando C. N. Per...
ProLiV - Animated Process-modeler of Complex (Computational) Linguistic Methods and Theories - is a fully modular, flexible, XML-based stand-alone Java application, used for compu...
We propose a framework for estimation and analysis of temporal facial expression patterns of a speaker. The proposed system aims to learn personalized elementary dynamic facial ex...
Ferda Ofli, Engin Erzin, Yucel Yemez, A. Murat Tek...
In photometric stereo a robust method is required to deal with outliers, such as shadows and non-Lambertian reflections. In this paper we rely on a probabilistic imaging model tha...