In many real world applications, active selection of training examples can significantly reduce the number of labelled training examples to learn a classification function. Differ...
I describe a framework for interpreting Support Vector Machines (SVMs) as maximum a posteriori (MAP) solutions to inference problems with Gaussian Process priors. This probabilisti...
We consider a suboptimal solution path algorithm for the Support Vector Machine. The solution path algorithm is an effective tool for solving a sequence of a parametrized optimiz...
The one-class and cost-sensitive support vector machines (SVMs) are state-of-the-art machine learning methods for estimating density level sets and solving weighted classificatio...
Background: Synthesis of data from published human genetic association studies is a critical step in the translation of human genome discoveries into health applications. Although...
Wei Yu, Melinda Clyne, Siobhan M. Dolan, Ajay Yesu...