Multi-Task Time Series Forecasting With Shared Attention

@article{Chen2020MultiTaskTS,
  title={Multi-Task Time Series Forecasting With Shared Attention},
  author={Zekai Chen and E Jiaze and Xiao Zhang and Hao Sheng and Xiuzhen Cheng},
  journal={2020 International Conference on Data Mining Workshops (ICDMW)},
  year={2020},
  pages={917-925}
}
  • Zekai Chen, E. Jiaze, +2 authors Xiuzhen Cheng
  • Published 1 November 2020
  • Computer Science, Mathematics
  • 2020 International Conference on Data Mining Workshops (ICDMW)
Time series forecasting is a key component in many industrial and business decision processes and recurrent neural network (RNN) based models have achieved impressive progress on various time series forecasting tasks. However, most of the existing methods focus on single-task forecasting problems by learning separately based on limited supervised objectives, which often suffer from insufficient training instances. As the Transformer architecture and other attention-based models have… Expand

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