ML Anthology

Fast Algorithm for Non-Stationary Gaussian Process Prediction

Yulai Zhang, Guiming Luo
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/}
}