The proposed method achieves online learning and prediction in real-time. Com- parisons with other non-parametric regression methods show that LGP has higher.
Inspired by local learning, we propose a method to speed up standard Gaussian Process regression (GPR) with local GP models (LGP). The training data is ...
This work proposes a method to speed up standard Gaussian process regression with local GP models (LGP), which has higher accuracy than LWPR and close to ...
Learning in real-time applications, e.g., online approximation of the inverse dy- namics model for model-based robot control, requires fast online ...
This approach offers a natural framework to incorporate unknown nonlinearities as well as to continually adapt online for changes in the robot dynamics. However ...
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AutoDJ uses Gaus-sian Process Regression to learn a user preference function over songs. This function takes music metadata as inputs. This paper further ...
Peters, “Local gaussian process regression for real time online model learning and control,” in Advances in Neural Information Processing Systems, Vancouver,.
Dec 8, 2008 · Inspired by local learning, we propose a method to speed up standard Gaussian process regression (GPR) with local GP models (LGP). The training ...
Inspired by locally linear regression techniques, we propose an approximation to the standard GPR using local Gaussian processes models inspired by. Due to ...
A local approximation to the standard GPR, called local GPR (LGP), is proposed for real-time model online learning by combining the strengths of both ...