Abstract. This paper considers the sensor network localization problem using signal strength. Unlike range-based methods signal strength information is stored in a kernel matrix. L...
Kernel regression is an effective tool for a variety of image processing tasks such as denoising and interpolation [1]. In this paper, we extend the use of kernel regression for de...
Recently, instead of selecting a single kernel, multiple kernel learning (MKL) has been proposed which uses a convex combination of kernels, where the weight of each kernel is opt...
Electric grids are moving from a centralized single supply chain towards a decentralized bidirectional grid of suppliers and consumers in an uncertain and dynamic scenario. Soon, t...
In kernel-based regression learning, optimizing each kernel individually is useful when the data density, curvature of regression surfaces (or decision boundaries) or magnitude of...