When equipped with kernel functions, online learning algorithms are susceptible to the "curse of kernelization" that causes unbounded growth in the model size. To addres...
Background: This paper introduces the notion of optimizing different norms in the dual problem of support vector machines with multiple kernels. The selection of norms yields diff...
We classify 3D aerial LiDAR scattered height data into buildings, trees, roads, and grass using the Support Vector Machine (SVM) algorithm. To do so we use five features: height, ...
Suresh K. Lodha, Edward J. Kreps, David P. Helmbol...
Platt’s probabilistic outputs for Support Vector Machines (Platt, 2000) has been popular for applications that require posterior class probabilities. In this note, we propose an ...
Abstract— We address the problem of human motion recognition in this paper. The goal of human motion recognition is to recognize the type of motion recorded in a video clip, whic...