This paper introduces a machine learning approach into the process of direct volume rendering of biomedical highresolution 3D images. More concretely, it proposes a learning pipel...
The k-Nearest Neighbors algorithm can be easily adapted to classify complex objects (e.g. sets, graphs) as long as a proper dissimilarity function is given over an input space. Bo...
Adam Woznica, Alexandros Kalousis, Melanie Hilario
Many kernel learning methods have to assume parametric forms for the target kernel functions, which significantly limits the capability of kernels in fitting diverse patterns. Som...
In this paper, we address the issue of learning nonlinearly separable concepts with a kernel classifier in the situation where the data at hand are altered by a uniform classific...
Inductive inference is concerned with algorithmic learning of recursive functions. In the model of learning in the limit a learner successful for a class of recursive functions mus...