Kernel methods have been applied successfully in many data mining tasks. Subspace kernel learning was recently proposed to discover an effective low-dimensional subspace of a kern...
Jianhui Chen, Shuiwang Ji, Betul Ceran, Qi Li, Min...
Multi-label problems arise in various domains such as multitopic document categorization and protein function prediction. One natural way to deal with such problems is to construc...
The kernel function plays a central role in kernel methods. In this paper, we consider the automated learning of the kernel matrix over a convex combination of pre-specified kerne...
The processes by which communities come together, attract new members, and develop over time is a central research issue in the social sciences -- political movements, professiona...
Lars Backstrom, Daniel P. Huttenlocher, Jon M. Kle...
Commercial relational databases currently store vast amounts of real-world data. The data within these relational repositories are represented by multiple relations, which are int...