Active set methods for training the Support Vector Machines (SVM) are advantageous since they enable incremental training and, as we show in this research, do not exhibit exponent...
Christopher Sentelle, Georgios C. Anagnostopoulos,...
In this paper, a novel approach for contour-based 2D shape recognition is proposed, using a recently introduced class of information theoretic kernels. This kind of kernels, based...
Manuele Bicego, André Filipe Torres Martins, Vitt...
Protein-protein interaction plays critical roles in cellular functions. In this work, we propose a computational method to predict protein-protein interaction by using support vec...
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 ...
We introduce a new family of positive-definite kernels for large margin classification in support vector machines (SVMs). These kernels mimic the computation in large neural netwo...