This paper describes a framework to construct interface agents with example dialogs based on the tasks by the machine learning technology. The Wizard of Oz method is used to collec...
During past few years, a variety of methods have been developed for learning probabilistic networks from data, among which the heuristic single link forward or backward searches ar...
In the paper we propose a new type of regularization procedure for training sparse Bayesian methods for classification. Transforming Hessian matrix of log-likelihood function to d...
Many real-world domains present the problem of imbalanced data sets, where examples of one classes significantly outnumber examples of other classes. This makes learning difficu...
Despite the recent resurgence of interest in learning methods for planning, most such efforts are still focused exclusively on classical planning problems. In this work, we invest...