An adaptive and iterative LSSVR algorithm based on quadratic Renyi entropy is presented in this paper. LS-SVM loses the sparseness of support vector which is one of the important ...
Kernel methods yield state-of-the-art performance in certain applications such as image classification and object detection. However, large scale problems require machine learning...
Sreekanth Vempati, Andrea Vedaldi, Andrew Zisserma...
We propose a simple yet potentially very effective way of visualizing trained support vector machines. Nomograms are an established model visualization technique that can graphica...
Aleks Jakulin, Martin Mozina, Janez Demsar, Ivan B...
Abstract— The optimal model parameters of a kernel machine are typically given by the solution of a convex optimisation problem with a single global optimum. Obtaining the best p...
Similarity search methods are widely used as kernels in various data mining and machine learning applications including those in computational biology, web search/clustering. Near...