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Data-driven solutions to Electric Vehicle (EV) range estimation is attracting attention recently due to the prevalence of Internet of Things (IoT). However, there raise the Big Data problems with the increased volume and number of sensory sources of unstructured data collected from the EV equipped with In-Vehicle Networks. This means that traditional statistical analysis and Machine Learning tools...
As a supervised learning algorithm, the standard Gaussian processes has the excellent performance of classification. In this paper, we present a semi-supervised algorithm to learning a Gaussian process classifier, which incorporating a graph-based construction of semi-supervised kernels in the presence of labeled and unlabeled data, and expanding the standard Gaussian processes algorithm into the...
Visualization of uncertainty or error in astrophysical data is seldom available in simulations of astronomical phenomena, and yet almost all rendered attributes possess some degree of uncertainty due to observational error. Uncertainties associated with spatial location typically vary significantly with scale and thus introduce further complexity in the interpretation of a given visualization. This...
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