Online variational Gaussian process for time series data
Abstract Gaussian processes (GPs) are a powerful and popular framework for addressing machine learning problems, particularly for time-dependent data such as that generated by the Internet of Things (IoT). GPs offer a compelling choice for constructing real-valued nonlinear models due to their inher...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2024-12-01
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| Series: | Journal of Big Data |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s40537-024-01005-5 |
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