Abox inference is an important part in OWL data management. When involving large scale of instance data, it can not be supported by existing inference engines. In this paper, we p...
We define an inference system to capture explanations based on causal statements, using an ontology in the form of an IS-A hierarchy. We first introduce a simple logical language...
Philippe Besnard, Marie-Odile Cordier, Yves Moinar...
Bias/variance analysis is a useful tool for investigating the performance of machine learning algorithms. Conventional analysis decomposes loss into errors due to aspects of the le...
This paper presents a new approach to inference in Bayesian networks. The principal idea is to encode the network by logical sentences and to compile the resulting encoding into an...
We present a new hybrid algorithm for local search in distributed combinatorial optimization. This method is a mix between classical local search methods in which nodes take decis...
Abstract. Computational inference of transcriptional regulatory networks remains a challenging problem, in part due to the lack of strong network models. In this paper we present e...
RDFKB (Resource Description Framework Knowledge Base) is a relational database system for RDF datasets which supports inference and knowledge management. Significant research has ...
We investigate a hybrid method which improves the quality of state inference and parameter estimation in blind deconvolution of a sparse source modeled by a Bernoulli-Gaussian pro...
New Web 2.0 applications, with their emphasis on collaboration and communication, hold the promise of major advances in social connectivity and coordination; however, they also in...
Sara Motahari, Sotirios G. Ziavras, Richard P. Sch...