ion levels. The framework also supports the generation of test constraints, which can be satisfied using a constraint solver to generate tests. A compositional verification approac...
— In this work, a probabilistic model is established for recurrent networks. The EM (expectation-maximization) algorithm is then applied to derive a new fast training algorithm f...
In this paper the sequential prediction problem with expert advice is considered for the case where losses of experts suffered at each step cannot be bounded in advance. We presen...
Abstract. Since testing is inherently incomplete, test selection is of vital importance. Coverage measures evaluate the quality of a test suite and help the tester select test case...
Recent text and speech processing applications such as speech mining raise new and more general problems related to the construction of language models. We present and describe in...