Constrained clustering has been well-studied for algorithms like K-means and hierarchical agglomerative clustering. However, how to encode constraints into spectral clustering rem...
Much work on skewed, stochastic, high dimensional, and biased datasets usually implicitly solve each problem separately. Recently however, we have been approached by Texas Commiss...
Kun Zhang, Wei Fan, Xiaojing Yuan, Ian Davidson, X...
Nowadays, the classification of graph data has become an important and active research topic in the last decade, which has a wide variety of real world applications, e.g. drug acti...
Mobile devices are becoming increasingly sophisticated and the latest generation of smart cell phones now incorporates many diverse and powerful sensors. These sensors include GPS...
Our research addresses two important problems that arise in modern large-scale distributed systems: (1) the necessity to virtualize their data flows by applying actions such as ï...
Radhika Niranjan, Ada Gavrilovska, Karsten Schwan,...