The existence of good probabilistic models for the job arrival process and the delay components introduced at different stages of job processing in a Grid environment is important ...
We develop a framework for analyzing security protocols in which protocol adversaries may be arbitrary probabilistic polynomial-time processes. In this framework, protocols are wr...
Patrick Lincoln, John C. Mitchell, Mark Mitchell, ...
We give a fast and practical algorithm for statistical learning hyperparameters from observable data in probabilistic image processing, which is based on Gaussian graphical model ...
Probabilistic Latent Semantic Analysis (PLSA) is one of the most popular statistical techniques for the analysis of two-model and co-occurrence data. It has applications in inform...
We propose a new approach for automatic melody extraction from polyphonic audio, based on Probabilistic Latent Component Analysis (PLCA). An audio signal is first divided into vo...