This paper presents an application of the general sample-to-object approach to the problem of invariant image classification. The approach results in defining new SVM kernels base...
: A novel support vector machine method for classification is presented in this paper. A modified kernel function based on the similarity metric and Riemannian metric is applied ...
In order to overcome the computation and storage problem for large-scale data set, an efficient iterative method of Generalized Discriminant Analysis is proposed. Because sample v...
The computation and memory required for kernel machines with N training samples is at least O(N2 ). Such a complexity is significant even for moderate size problems and is prohibi...
Changjiang Yang, Ramani Duraiswami, Larry S. Davis
In kernel methods, an interesting recent development seeks to learn a good kernel from empirical data automatically. In this paper, by regarding the transductive learning of the k...