In this paper, we provide new complexity results for algorithms that learn discrete-variable Bayesian networks from data. Our results apply whenever the learning algorithm uses a ...
David Maxwell Chickering, Christopher Meek, David ...
The use of Bayesian networks for classification problems has received significant recent attention. Although computationally efficient, the standard maximum likelihood learning me...
It is common to view programs as a combination of logic and control: the logic part de nes what the program must do, the control part how to do it. The Logic Programming paradigm ...
—The paper presents a methodology that combines statistical learning with constraint optimization by locally optimizing Radio Resource Management (RRM) or system parameters of po...
Moazzam Islam Tiwana, Zwi Altman, Berna Sayra&cced...
—The length of test cases is a little investigated topic in search-based test generation for object oriented software, where test cases are sequences of method calls. While intui...