We apply robust Bayesian decision theory to improve both generative and discriminative learners under bias in class proportions in labeled training data, when the true class propo...
Current research in the area of manufacturing planning and control has moved away from traditional centralized solutions towards distributed architectures that range from hierarch...
A programming language that lacks facilities for concurrent programming can gain those facilities in two ways: the language can be extended with additional constructs, which will ...
This paper describes a model for generating time series which exhibit the statistical phenomenon known as long-range dependence (LRD). A Markov Modulated Process based upon an inf...
Learning patterns of human behavior from sensor data is extremely important for high-level activity inference. We show how to extract a person’s activities and significant plac...