RPMixer: Shaking Up Time Series Forecasting with Random Projections for Large Spatial-Temporal Data

Author:

Yeh Chin-Chia Michael1ORCID,Fan Yujie1ORCID,Dai Xin1ORCID,Saini Uday Singh1ORCID,Lai Vivian1ORCID,Aboagye Prince Osei1ORCID,Wang Junpeng1ORCID,Chen Huiyuan1ORCID,Zheng Yan1ORCID,Zhuang Zhongfang1ORCID,Wang Liang1ORCID,Zhang Wei1ORCID

Affiliation:

1. Visa Research, Foster City, CA, USA

Publisher

ACM

Reference68 articles.

1. Anthony Bagnall, Jason Lines, Aaron Bostrom, James Large, and Eamonn Keogh. 2017. The great time series classification bake off: a review and experimental evaluation of recent algorithmic advances. Data mining and knowledge discovery, Vol. 31 (2017), 606--660.

2. Lei Bai, Lina Yao, Can Li, Xianzhi Wang, and Can Wang. 2020. Adaptive graph convolutional recurrent network for traffic forecasting. Advances in neural information processing systems, Vol. 33 (2020), 17804--17815.

3. Random projection in dimensionality reduction

4. Zekun Cai, Renhe Jiang, Xinyu Yang, Zhaonan Wang, Diansheng Guo, Hiroki Kobayashi, Xuan Song, and Ryosuke Shibasaki. 2023. MemDA: Forecasting Urban Time Series with Memory-based Drift Adaptation. arXiv preprint arXiv:2309.14216 (2023).

5. Random-projection ensemble classification

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