Abstract. This paper investigates the methods for learning predictive classifiers based on Bayesian belief networks (BN) – primarily unrestricted Bayesian networks and Bayesian m...
In this paper we present a new method of integrating the placement and routing stages in the physical design of channel-based architectures, and present the first implementation o...
Complexity-penalization strategies are one way to decide on the most appropriate network size in order to address the trade-off between overfitted and underfitted models. In this p...
In this paper we develop a variant of a previously proposed method the regenerative randomization method for the transient analysis of dependability performability models. The va...
Abstract. In order to escape from local optima, it is standard practice to periodically restart a genetic algorithm according to some restart criteria/policy. This paper addresses ...