Abstract. Classification of structured data (i.e., data that are represented as graphs) is a topic of interest in the machine learning community. This paper presents a different,...
Existing meta-learning based distributed data mining approaches do not explicitly address context heterogeneity across individual sites. This limitation constrains their applicatio...
Yan Xing, Michael G. Madden, Jim Duggan, Gerard Ly...
—We consider resource allocation for distributed streaming applications running in a grid environment, where continuously streaming data needs to be aggregated and processed to p...
We analyze a massive social network, gathered from the records of a large mobile phone operator, with more than a million users and tens of millions of calls. We examine the distr...
Uncertainty is a popular phenomenon in machine learning and a variety of methods to model uncertainty at different levels has been developed. The aim of this paper is to motivate ...