Extracting predictive information from heterogeneous data streams using Gaussian Processes
Financial markets are notoriously complex environments, presenting vast amounts of noisy, yet potentially informative data. We consider the problem of forecasting financial time series from a wide range of information sources using online Gaussian Processes with Automatic Relevance Determination (AR...
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| Format: | Journal article |
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IOS Press
2016
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