Naive Bayes is an effective and efficient learning algorithm in classification. In many applications, however, an accurate ranking of instances based on the class probability is m...
Inductive learning of first-order theory based on examples has serious bottleneck in the enormous hypothesis search space needed, making existing learning approaches perform poorl...
This paper addresses the problem of classification in situations where the data distribution is not homogeneous: Data instances might come from different locations or times, and t...
This paper presents a general method to derive tight rates of convergence for numerical approximations in optimal control when we consider variable resolution grids. We study the ...
Program specifications are important in many phases of the software development process, but they are often omitted or incomplete. An important class of specifications takes the f...