We present a new method for nonlinear prediction of discrete random sequences under minimal structural assumptions. We give a mathematical construction for optimal predictors of s...
This paper introduces a novel statistical mixture model for probabilistic clustering of histogram data and, more generally, for the analysis of discrete co occurrence data. Adoptin...
This paper deals with the total variation minimization problem in image restoration for convex data fidelityfunctionals.Weproposeanewandfastalgorithmwhichcomputesanexactsolutionint...
Ensemble learning is a variational Bayesian method in which an intractable distribution is approximated by a lower-bound. Ensemble learning results in models with better generaliz...
This paper presents a message-based discrete event simulation architecture. It will examine each of the different types of messages used to schedule events, transfer items through...