We introduce a new algorithm based on linear programming that approximates the differential value function of an average-cost Markov decision process via a linear combination of p...
We study the partitioning of temporal planning problems formulated as mixed-integer nonlinear programming problems, develop methods to reduce the search space of partitioned subpr...
This paper concerns problem of selection of optimal subset of irredundant unconditional diagnostic tests by means of evolutionary approach. The method of correction of features’...
This paper presents a method for learning a distance metric from relative comparison such as “A is closer to B than A is to C”. Taking a Support Vector Machine (SVM) approach,...
Abstract. Data sets in large applications are often too massive to t completely inside the computer's internal memory. The resulting input output communication or I O between ...