In the present paper, by applying the theory of stochastic processes and interacting particle systems and models, including stopping time theory and stochastic voter model, we mode...
Abstract— Particle filters are a frequently used filtering technique in the robotics community. They have been successfully applied to problems such as localization, mapping, o...
Cyrill Stachniss, Giorgio Grisetti, Wolfram Burgar...
This paper proposes a hierarchical Bayesian model that can be used for semi-supervised hyperspectral image unmixing. The model assumes that the pixel reflectances result from linea...
Nicolas Dobigeon, Jean-Yves Tourneret, Chein-I Cha...
This paper presents a framework for maximum a posteriori (MAP) speaker adaptation of state duration distributions in hidden Markov models (HMM). Four key issues of MAP estimation, ...
Statistical language modeling has been successfully used for speech recognition, part-of-speech tagging, and syntactic parsing. Recently, it has also been applied to information r...