This contribution develops a theoretical framework that takes into account the effect of approximate optimization on learning algorithms. The analysis shows distinct tradeoffs for...
In this paper we propose algorithms for combining and ranking answers from distributed heterogeneous data sources in the context of a multi-ontology Question Answering task. Our pr...
- Many research questions remain open with regard to improving reliability in exascale systems. Among others, statistics-based analysis has been used to find anomalies, to isolate ...
Line C. Pouchard, Jonathan D. Dobson, Stephen W. P...
A powerful approach to search is to try to learn a distribution of good solutions (in particular of the dependencies between their variables) and use this distribution as a basis ...
Network resources will always be heterogeneous, and thus have different functionalities and programming models. This adversely affects interoperability. Seamless Mobility is one e...