We review a multiple kernel learning (MKL) technique called p regularised multiple kernel Fisher discriminant analysis (MK-FDA), and investigate the effect of feature space denois...
Selecting the optimal kernel is an important and difficult challenge in applying kernel methods to pattern recognition. To address this challenge, multiple kernel learning (MKL) ...
In this paper, we propose a group-sensitive multiple kernel learning (GS-MKL) method to accommodate the intra-class diversity and the inter-class correlation for object categoriza...
Recent research on multiple kernel learning has lead to a number of approaches for combining kernels in regularized risk minimization. The proposed approaches include different for...
Simple features constructed from order book data for the EURUSD currency pair were used to construct a set of kernels. These kernels were used both individually and simultaneously...
Tristan Fletcher, Zakria Hussain, John Shawe-Taylo...