Our shared belief is that learning, like other human activities, cannot and will not be confined within rigidly defined course systems or learning repositories, inclosing learning...
Mohamed Amine Chatti, Ralf Klamma, Christoph Quix,...
We propose a graph-based semi-supervised symmetric matching framework that performs dense matching between two uncalibrated wide-baseline images by exploiting the results of sparse...
Jianxiong Xiao, Jingni Chen, Dit-Yan Yeung, Long Q...
Abstract. Capturing regularities in high-dimensional data is an important problem in machine learning and signal processing. Here we present a statistical model that learns a nonli...
Despite serious research efforts, automatic ontology matching still suffers from severe problems with respect to the quality of matching results. Existing matching systems trade-of...
Kai Eckert, Christian Meilicke, Heiner Stuckenschm...
We consider a new data mining problem of detecting the members of a rare class of data, the needles, that have been hidden in a set of records, the haystack. Besides the haystack, ...