Past empirical work has shown that learning multiple related tasks from data simultaneously can be advantageous in terms of predictive performance relative to learning these tasks...
Maximum Variance Unfolding (MVU) and its variants have been very successful in embedding data-manifolds in lower dimensionality spaces, often revealing the true intrinsic dimensio...
Nikolaos Vasiloglou, Alexander G. Gray, David V. A...
In this work, a new algorithm is proposed for fast estimation of nonparametric multivariate kernel density, based on principal direction divisive partitioning (PDDP) of the data s...
Background: Recent discoveries of a large variety of important roles for non-coding RNAs (ncRNAs) have been reported by numerous researchers. In order to analyze ncRNAs by kernel ...
Motivation: Remote homology detection between protein sequences is a central problem in computational biology. Supervised learning algorithms based on support vector machines are ...