Learning temporal causal structures between time series is one of the key tools for analyzing time series data. In many real-world applications, we are confronted with Irregular T...
With the growth of the Internet and E-commerce, bipartite rating networks are ubiquitous. In such bipartite rating networks, there exist two types of entities: the users and the o...
Feature selection is widely used in preparing highdimensional data for effective data mining. Increasingly popular social media data presents new challenges to feature selection....
Many animals produce long sequences of vocalizations best described as “songs.” In some animals, such as crickets and frogs, these songs are relatively simple and repetitive c...
Jesin Zakaria, Sarah Rotschafer, Abdullah Mueen, K...
Droughts are one of the most damaging climate-related hazards. The late 1960s Sahel drought in Africa and the North American Dust Bowl of the 1930s are two examples of severe drou...
Qiang Fu, Arindam Banerjee, Stefan Liess, Peter K....
Kernel summations are a ubiquitous key computational bottleneck in many data analysis methods. In this paper, we attempt to marry, for the first time, the best relevant technique...
Dongryeol Lee, Richard W. Vuduc, Alexander G. Gray
Link prediction is an important task in social networks and data mining for understanding the mechanisms by which the social networks form and evolve. In most link prediction rese...
Low-rank approximations which are computed from selected rows and columns of a given data matrix have attracted considerable attention lately. They have been proposed as an altern...
Christian Thurau, Kristian Kersting, Christian Bau...