Abstract. We present a survey of recent results concerning the theoretical and empirical performance of algorithms for learning regularized least-squares classifiers. The behavior ...
Clustering aims to find useful hidden structures in data. In this paper we present a new clustering algorithm that builds upon the consistency method (Zhou, et.al., 2003), a semi-...
Abstract. Time Petri Nets (TPN) and Timed Automata (TA) are widely-used formalisms for the modeling and analysis of timed systems. A recently-developed approach for the analysis of...
A standard method for approximating averages in probabilistic models is to construct a Markov chain in the product space of the random variables with the desired equilibrium distr...
Numerous applications of data mining to scientific data involve the induction of a classification model. In many cases, the collection of data is not performed with this task in m...