This paper presents a new method for multiple structure segmentation, using a maximum a posteriori (MAP) estimation framework, based on prior shape densities involving nonparametr...
We o er a simple paradigm for tting models, parametric and non-parametric, to noisy data, which resolves some of the problems associated with classic MSE algorithms. This is done ...
One of the key tasks for analyzing conversational data is segmenting it into coherent topic segments. However, most models of topic segmentation ignore the social aspect of conver...
Viet-An Nguyen, Jordan L. Boyd-Graber, Philip Resn...
We investigate the problem of acoustic modeling in which prior language-specific knowledge and transcribed data are unavailable. We present an unsupervised model that simultaneou...
?This paper presents a computational paradigm called Data-Driven Markov Chain Monte Carlo (DDMCMC) for image segmentation in the Bayesian statistical framework. The paper contribut...