In this paper we introduce a new approach to controlling error in hierarchical clustering algorithms for radiosity. The new method ensures that just enough work is done to meet th...
This article presents and analyzes algorithms that systematically generate random Bayesian networks of varying difficulty levels, with respect to inference using tree clustering. ...
Strategies are developed for “fattening” the tasks of computation-dags so as to accommodate the heterogeneity of remote clients in Internet-based computing (IC). Earlier work ...
Abstract— This paper describes a novel algorithm for autonomous and incremental learning of motion pattern primitives by observation of human motion. Human motion patterns are ed...
Abstract. This paper addresses the clustering problem of hidden dynamical systems behind observed multivariate sequences by assuming an interval-based temporal structure in the seq...