Markov chains are widely used in the context of performance and reliability evaluation of systems of various nature. Model checking of such chains with respect to a given (branchin...
Holger Hermanns, Joost-Pieter Katoen, Joachim Meye...
Standard inductive learning requires that training and test instances come from the same distribution. Transfer learning seeks to remove this restriction. In shallow transfer, tes...
Web forums have become an important data resource for many web applications, but extracting structured data from unstructured web forum pages is still a challenging task due to bo...
Jiang-Ming Yang, Rui Cai, Yida Wang, Jun Zhu, Lei ...
We extend the theory of labeled Markov processes with internal nondeterminism, a fundamental concept for the further development of a process theory with abstraction on nondetermi...
This paper addresses the question of how statistical learning algorithms can be integrated into a larger AI system both from a practical engineering perspective and from the persp...