During software evolution, adaptive, and corrective maintenance are common reasons for changes. Often such changes cluster around key components. It is therefore important to anal...
James M. Bieman, Anneliese Amschler Andrews, Helen...
A major problem in machine learning is that of inductive bias: how to choose a learner's hypothesis space so that it is large enough to contain a solution to the problem bein...
This paper presents an attempt of using intelligent agents for testing and repairing a distributed system, whose elements may or may not have embedded BIST (Built-In Self-Test) an...
Abstract. The notion of user preference in database modeling has recently received much attention in advanced applications, such as personalization of e-services, since it captures...
In solving complex visual learning tasks, adopting multiple descriptors to more precisely characterize the data has been a feasible way for improving performance. These representa...