When given a small sample, we show that classification with SVM can be considerably enhanced by using a kernel function learned from the training data prior to discrimination. Thi...
Identifying the appropriate kernel function/matrix for a given dataset is essential to all kernel-based learning techniques. A variety of kernel learning algorithms have been prop...
Kernel coupling refers to the effect that kernel i has on kernel j in relation to running each kernel in isolation. The two kernels can correspond to adjacent kernels or a chain ...
Jonathan Geisler, Valerie E. Taylor, Xingfu Wu, Ri...
This paper proposes a convolution forest kernel to effectively explore rich structured features embedded in a packed parse forest. As opposed to the convolution tree kernel, the p...
Operations on spatial objects have much individuality. As a consequence, the spatial data modelling approaches, which have been proposed, have to consider either data types of the...