We present an algorithm which partitions a data set in two parts with equal size and experimentally nearly the same distribution measured through the likelihood of a Parzen kernel ...
We introduce a semi-supervised learning estimator which tends to the first kernel principal component as the number of labeled points vanishes. We show application of the proposed...
Leonardo Angelini, Daniele Marinazzo, Mario Pellic...
Recent advances in Multiple Kernel Learning (MKL) have positioned it as an attractive tool for tackling many supervised learning tasks. The development of efficient gradient desce...
Abstract--Kernel-based algorithms such as support vector machines have achieved considerable success in various problems in batch setting, where all of the training data is availab...
Jyrki Kivinen, Alex J. Smola, Robert C. Williamson
Crown structures in a graph are defined and shown to be useful in kernelization algorithms for the classic vertex cover problem. Two vertex cover kernelization methods are discus...
Faisal N. Abu-Khzam, Michael R. Fellows, Michael A...