Kernels are two-placed functions that can be interpreted as inner products in some Hilbert space. It is this property which makes kernels predestinated to carry linear models of l...
While classical kernel-based learning algorithms are based on a single kernel, in practice it is often desirable to use multiple kernels. Lanckriet et al. (2004) considered conic ...
Abstract. Electromagnetic navigation bronchoscopy requires the accurate registration of a preinterventional computed tomography (CT) image to the coordinate system of the electroma...
Marco Feuerstein, Takamasa Sugiura, Daisuke Deguch...
Abstract. Surface-based morphometry (SBM) is widely used in biomedical imaging and other domains to localize shape changes related to different conditions. This paper presents a co...
Jing Wan, Li Shen, Shiaofen Fang, Jason McLaughlin...
—Previous studies have demonstrated that document clustering performance can be improved significantly in lower dimensional linear subspaces. Recently, matrix factorization base...