Abstract. We propose a novel method for addressing the model selection problem in the context of kernel methods. In contrast to existing methods which rely on hold-out testing or t...
We propose a fast iterative classification algorithm for Kernel Fisher Discriminant (KFD) using heterogeneous kernel models. In contrast with the standard KFD that requires the us...
In this paper, we present a novel multiple kernel method to learn the optimal classification function for visual concept. Although many carefully designed kernels have been propose...
It is generally believed that quadratic discriminant analysis (QDA) can better fit the data in practical pattern recognition applications compared to linear discriminant analysis ...
Jie Wang, Konstantinos N. Plataniotis, Juwei Lu, A...
Convolution kernels, such as sequence and tree kernels, are advantageous for both the concept and accuracy of many natural language processing (NLP) tasks. Experiments have, howev...