kernlab is an extensible package for kernel-based machine learning methods in R. It takes advantage of R's new S4 ob ject model and provides a framework for creating and using k...
We give a basic introduction to Gaussian Process regression models. We focus on understanding the role of the stochastic process and how it is used to define a distribution over...
We consider the problem of multi-step ahead prediction in time series analysis using the non-parametric Gaussian process model. k-step ahead forecasting of a discrete-time non-l...
Extending the forecasting time is a critical demand for real applications,\nsuch as extreme weather early warning and long-term energy consumption\nplanning. This paper studies ...
Generalization bounds depending on the margin of a classifier are a relatively new development. They provide an explanation of the performance of state-of-the-art learning syste...
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