High-dimensional data usually incur learning deficiencies and computational difficulties. We present a novel semi-supervised dimensionality reduction technique that embeds high-dim...
Background: The prediction of protein-protein interactions is an important step toward the elucidation of protein functions and the understanding of the molecular mechanisms insid...
Martial Hue, Michael Riffle, Jean-Philippe Vert, W...
Background: Classification of protein sequences is a central problem in computational biology. Currently, among computational methods discriminative kernel-based approaches provid...
We propose a new method for clustering based on finding maximum margin hyperplanes through data. By reformulating the problem in terms of the implied equivalence relation matrix, ...
Linli Xu, James Neufeld, Bryce Larson, Dale Schuur...
A sparse representation of Support Vector Machines (SVMs) with respect to input features is desirable for many applications. In this paper, by introducing a 0-1 control variable t...