This paper analyzes the potential advantages and theoretical challenges of “active learning” algorithms. Active learning involves sequential sampling procedures that use infor...
We present a robust algorithm for independent component analysis that uses the sum of marginal quadratic negentropies as a dependence measure. It can handle arbitrary source densit...
Abstract. This paper empirically explores the advantages of the collaboration between different parallel compute sites in a decentralized grid scenario. To this end, we assume ind...
Christian Grimme, Joachim Lepping, Alexander Papas...
The goal in domain adaptation is to train a model using labeled data sampled from a domain different from the target domain on which the model will be deployed. We exploit unlabel...
Schema matching is the task of matching between concepts describing the meaning of data in various heterogeneous, distributed data sources. With many heuristics to choose from, sev...