We develop new algorithms for designing matched wavelets and matched scaling functions using a new parametrization of compactly supported orthonormal wavelets that is developed in...
Kernel methods are effective approaches to the modeling of structured objects in learning algorithms. Their major drawback is the typically high computational complexity of kernel ...
Fabio Aiolli, Giovanni Da San Martino, Alessandro ...
Kernel regression techniques such as Relevance Vector Machine (RVM) regression, Support Vector Regression and Gaussian processes are widely used for solving many computer vision p...
In this paper we present preliminary results stemming from a novel application of Markov Models and Support Vector Machines to splice site classification of Intron-Exon and Exon-I...
Vertical partitioning is a well-known technique for optimizing query performance in relational databases. An extreme form of this technique, which we call vectorization, is to sto...
Peter Buneman, Byron Choi, Wenfei Fan, Robert Hutc...