The use of Mercer kernel methods in statistical learning theory provides for strong learning capabilities, as seen in kernel principal component analysis and support vector machin...
In this paper, we investigate the noise robustness of Wang and Shamma's early auditory (EA) model for the calculation of an auditory spectrum in audio classification applicati...
We propose a local, generative model for similarity-based classification. The method is applicable to the case that only pairwise similarities between samples are available. The c...
This paper presents an investigation into the combination of different classifiers for toxicity prediction. These classification methods involved in generating classifiers for comb...
String kernels directly model sequence similarities without the necessity of extracting numerical features in a vector space. Since they better capture complex traits in the seque...