Supervised classification methods have been shown to be very effective for a large number of applications. They require a training data set whose instances are labeled to indicate...
Learning to rank from relevance judgment is an active research area. Itemwise score regression, pairwise preference satisfaction, and listwise structured learning are the major te...
Soumen Chakrabarti, Rajiv Khanna, Uma Sawant, Chir...
Record label companies would like to identify potential artists as early as possible in their careers, before other companies approach the artists with competing contracts. The va...
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...
A good distance metric is crucial for many data mining tasks. To learn a metric in the unsupervised setting, most metric learning algorithms project observed data to a lowdimensio...