We applied a multiple kernel learning (MKL) method based on information-theoretic optimization to speaker recognition. Most of the kernel methods applied to speaker recognition sy...
Tetsuji Ogawa, Hideitsu Hino, Nima Reyhani, Noboru...
The choice of the kernel function which determines the mapping between the input space and the feature space is of crucial importance to kernel methods. The past few years have se...
Multicore processors are marking the beginning of a new era of computing where massive parallelism is available and necessary. Slightly slower but easy to parallelize kernels are ...
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...
Online learning and kernel learning are two active research topics in machine learning. Although each of them has been studied extensively, there is a limited effort in addressing ...