Local Gaussian Process Regression for Real Time Online Model Learning

NeurIPS 2008 Duy Nguyen-TuongJan R. PetersMatthias Seeger

Learning in real-time applications, e.g., online approximation of the inverse dynamics model for model-based robot control, requires fast online regression techniques. Inspired by local learning, we propose a method to speed up standard Gaussian Process regression (GPR) with local GP models (LGP)... (read more)

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