This paper presents a new algorithm named Kernel Bisecting k-means and Sample Removal (KBK-SR) as a sampling preprocessing for SVM training to improve the scalability. The novel c...
— We propose a powerful symmetric kernel classifier for nonlinear detection in challenging rank-deficient multipleantenna aided communication systems. By exploiting the inheren...
Sheng Chen, Andreas Wolfgang, Chris J. Harris, Laj...
Abstract— During the last years, high throughput experiments have become very popular. During the analysis of such data the need for a functional grouping of genes arises. In thi...
Support Vector Machines (SVMs) have been very successful in text classification. However, the intrinsic geometric structure of text data has been ignored by standard kernels commo...
Abstract. We propose a new string kernel based on variable-lengthdon't-care patterns (VLDC patterns). A VLDC pattern is an element of ({}) , where is an alphabet and is the ...