Abstract. This paper is concerned with designing architectures for rational agents. In the proposed architecture, agents have belief bases that are theories in a multi-modal, highe...
Abstract. We present a new method for voting exponential (in the number of attributes) size sets of Bayesian classifiers in polynomial time with polynomial memory requirements. Tra...
Abstract—In this paper, we present NetQuest, a flexible framework for large-scale network measurement. We apply Bayesian experimental design to select active measurements that m...
Abstract. The needs of efficient and flexible information retrieval on multistructural data stored in database and network are significantly growing. Especially, its flexibility pl...
Abstract. This paper investigates the methods for learning predictive classifiers based on Bayesian belief networks (BN) – primarily unrestricted Bayesian networks and Bayesian m...