It is difficult to learn good classifiers when training data is missing attribute values. Conventional techniques for dealing with such omissions, such as mean imputation, general...
Xiaoyuan Su, Taghi M. Khoshgoftaar, Russell Greine...
Abstract. We propose an algorithm for Sparse Bayesian Classification for multi-class problems using Automatic Relevance Determination(ARD). Unlike other approaches which treat mult...
—Cooperation between intrusion detection systems (IDSs) allows collective information and experience from a network of IDSs to be shared to improve the accuracy of detection. A c...
Carol J. Fung, Quanyan Zhu, Raouf Boutaba, Tamer B...
The efficient execution of irregular parallel applications on shared distributed systems requires novel approaches to scheduling, since both the application requirements and the sy...
In this paper we address the problem of learning the structure of a Bayesian network in domains with continuous variables. This task requires a procedure for comparing different c...