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Statistical learning theory answers these questions by deriving non-asymptotic bounds on the generalization error of a model or, in other words, by upper bounding the true error of the learned model based just on quantities computed on the available data.
This unique book discusses a selection of highly relevant topics in the Social Internet of Things (SIoT), including blockchain, fog computing and data fusion.
The aim of the conference was to bring together researchers and scientists, businesspeople and entrepreneurs, teachers, engineers, computer... Læs mere
This book discusses how to build optimization tools able to generate better future studies.
In turn, the last three parts are dedicated to applied topics and include papers on time series analysis in the earth sciences, energy time series forecasting, and time series analysis and prediction in other real-world problems.