This contribution develops a theoretical framework that takes into account the effect of approximate optimization on learning algorithms. The analysis shows distinct tradeoffs for...
Ontology learning integrates many complementary techniques, including machine learning, natural language processing, and data mining. Specifically, clustering techniques facilitat...
Online advertising is increasingly becoming more performance oriented, where the decision to show an advertisement to a user is made based on the user’s propensity to respond to...
Conditional Random Sampling (CRS) was originally proposed for efficiently computing pairwise (l2, l1) distances, in static, large-scale, and sparse data. This study modifies the o...
Location-based services and data mining algorithms analyzing objects moving on a complex traffic network are becoming increasingly important. In this paper, we introduce a new app...
Hans-Peter Kriegel, Peter Kunath, Martin Pfeifle, ...