Abstract--We investigate parameter-based and distributionbased approaches to regularizing the generative, similarity-based classifier called local similarity discriminant analysis ...
Background: The advent of the technology of DNA microarrays constitutes an epochal change in the classification and discovery of different types of cancer because the information ...
We propose a multiple source domain adaptation method, referred to as Domain Adaptation Machine (DAM), to learn a robust decision function (referred to as target classifier) for l...
: Laplacian Linear Discriminant Analysis (LapLDA) and Semi-supervised Discriminant Analysis (SDA) are two recently proposed LDA methods. They are developed independently with the a...
Most existing semi-supervised learning methods are based on the smoothness assumption that data points in the same high density region should have the same label. This assumption, ...