Existing work on similar sequence matching has focused on either whole matching or range subsequence matching. In this paper, we present novel methods for ranked subsequence match...
Most accurate predictions are typically obtained by learning machines with complex feature spaces (as e.g. induced by kernels). Unfortunately, such decision rules are hardly access...
We present a general boosting method extending functional gradient boosting to optimize complex loss functions that are encountered in many machine learning problems. Our approach...
The Gaussian process latent variable model (GP-LVM) is a powerful approach for probabilistic modelling of high dimensional data through dimensional reduction. In this paper we ext...
The problem of clustering is often addressed with techniques based on a Voronoi partition of the data space. Vector quantization is based on a similar principle, but it is a diffe...