In this paper, we introduce a generic framework for semi-supervised kernel learning. Given pairwise (dis-)similarity constraints, we learn a kernel matrix over the data that respe...
Abstract. Dynamic Pushdown Networks (DPNs) are a model for parallel programs with (recursive) procedures and process creation. The goal of this paper is to develop generic techniqu...
We introduce XPORT, a profile-driven distributed data dissemination system that supports an extensible set of data types, profile types, and optimization metrics. XPORT efficientl...
The UML goal of being a general-purpose modeling language discards the possibility to adopt too precise and strict a semantics. Users are to refine or define the semantics in th...
The problem of finding the most appropriate subset of features or regressors is the generic challenge of Machine Learning problems like regression estimation or pattern recognitio...