Background: This paper introduces the notion of optimizing different norms in the dual problem of support vector machines with multiple kernels. The selection of norms yields diff...
High-dimensional data usually incur learning deficiencies and computational difficulties. We present a novel semi-supervised dimensionality reduction technique that embeds high-dim...
Recent research has demonstrated quite convincingly that accurate cancer diagnosis can be achieved by constructing classifiers that are designed to compare the gene expression pro...
Balaji Krishnapuram, Lawrence Carin, Alexander J. ...
Heterogeneous entities or objects are very common and are usually interrelated with each other in many scenarios. For example, typical Web search activities involve multiple types...
The paper introduces a new framework for feature learning in classification motivated by information theory. We first systematically study the information structure and present a n...