A variational level set method is developed for the supervised classification problem. Nonlinear classifier decision boundaries are obtained by minimizing an energy functional tha...
We study the problem of image denoising where images are assumed to be samples from low dimensional (sub)manifolds. We propose the algorithm of locally linear denoising. The algor...
The goal of sufficient dimension reduction in supervised learning is to find the lowdimensional subspace of input features that is `sufficient' for predicting output values. ...
A large body of prior research on coreference resolution recasts the problem as a two-class classification problem. However, standard supervised machine learning algorithms that m...
:In this paper, a novel supervised dimensionality reduction method is developed based on both the correlation analysis and the idea of large margin learning. The method aims to m...