Abstract. In content-based image retrieval (CBIR) and image screening, it is often desirable to locate the regions of interest (ROI) in the images automatically. This can be accomp...
Yu-Feng Li, James T. Kwok, Ivor W. Tsang, Zhi-Hua ...
Abstract. Bayesian reinforcement learning (RL) is aimed at making more efficient use of data samples, but typically uses significantly more computation. For discrete Markov Decis...
In a set of access control policies, incompleteness is the existence of situations for which no policy applies. Some of these situations can be exploited by attackers, to obtain un...
Riaz Ahmed Shaikh, Kamel Adi, Luigi Logrippo, Serg...
This paper describes a novel data mining approach that employs evolutionary programming to discover knowledge represented in Bayesian networks. There are two different approaches ...
For some time, learning Bayesian networks has been both feasible and useful in many problems domains. Recently research has been done on learning equivalence classes of Bayesian n...