Forecasting Big Time Series: Theory and Practice

Forecasting Big Time Series: Theory and Practice. Faloutsos, C., Flunkert, V., Gasthaus, J., Januschowski, T., & Wang, Y. In Teredesai, A., Kumar, V., Li, Y., Rosales, R., Terzi, E., & Karypis, G., editors, Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, KDD 2019, Anchorage, AK, USA, August 4-8, 2019, pages 3209–3210, 2019. ACM.

Paper doi bibtex

@inproceedings{DBLP:conf/kdd/FaloutsosFGJW19,
  author       = {Christos Faloutsos and
                  Valentin Flunkert and
                  Jan Gasthaus and
                  Tim Januschowski and
                  Yuyang Wang},
  editor       = {Ankur Teredesai and
                  Vipin Kumar and
                  Ying Li and
                  R{\'{o}}mer Rosales and
                  Evimaria Terzi and
                  George Karypis},
  title        = {Forecasting Big Time Series: Theory and Practice},
  booktitle    = {Proceedings of the 25th {ACM} {SIGKDD} International Conference on
                  Knowledge Discovery {\&} Data Mining, {KDD} 2019, Anchorage, AK, USA,
                  August 4-8, 2019},
  pages        = {3209--3210},
  publisher    = {{ACM}},
  year         = {2019},
  url          = {https://doi.org/10.1145/3292500.3332289},
  doi          = {10.1145/3292500.3332289},
  timestamp    = {Thu, 28 Jul 2022 01:00:00 +0200},
  biburl       = {https://dblp.org/rec/conf/kdd/FaloutsosFGJW19.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

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