Fast Algorithm for Non-Stationary Gaussian Process Prediction

AAAI 2014 pp. 3150-3151

doi:10.1609/AAAI.V28I1.9080 /aaai/2014/zhang2014aaai-fast/

Abstract

Algorithm's time complexity is an essential issue for time series prediction in numerous practices.A novel fast exact inference method for Gaussian process model is proposed in this paper to accelerate the task of non-stationary time series prediction. Experiment was done on the real world power load data.

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Cite

Text

Zhang and Luo. "Fast Algorithm for Non-Stationary Gaussian Process Prediction." AAAI Conference on Artificial Intelligence, 2014. doi:10.1609/AAAI.V28I1.9080

Markdown

[Zhang and Luo. "Fast Algorithm for Non-Stationary Gaussian Process Prediction." AAAI Conference on Artificial Intelligence, 2014.](https://mlanthology.org/aaai/2014/zhang2014aaai-fast/) doi:10.1609/AAAI.V28I1.9080

BibTeX

@inproceedings{zhang2014aaai-fast,
  title     = {{Fast Algorithm for Non-Stationary Gaussian Process Prediction}},
  author    = {Zhang, Yulai and Luo, Guiming},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2014},
  pages     = {3150-3151},
  doi       = {10.1609/AAAI.V28I1.9080},
  url       = {https://mlanthology.org/aaai/2014/zhang2014aaai-fast/}
}