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English Information

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Authors
# Name
1 Samuel Torres(samuelrt@posgrad.lncc.br)
2 Raphael Saldanha(rfsaldanha@gmail.com)
3 Rocio Zorrilla(romizc@lncc.br)
4 Vitor Ribeiro(victorr@posgrad.lncc.br)
5 Eduardo Pena(eduardopena@utfpr.edu.br)
6 Fabio Porto(Fporto@lncc.br)

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Reference
# Reference
1 Castan-Lascorz, M., Jim´enez-Herrera, P., Troncoso, A., and Asencio-Cort´es, G. (2022). A new hybrid method for predicting univariate and multivariate time series based on pattern forecasting. Information Sciences, 586:611–627.
2 Cormen, T. H., Leiserson, C. E., Rivest, R. L., and Stein, C. (2022). Introduction to algorithms. MIT press
3 de Berg, M., Cheong, O., van Kreveld, M., and Overmars, M. (2008). Computational Geometry: Algorithms and Applications. Springer Berlin Heidelberg
4 Finkel, R. and Bentley, J. (1974). Quad trees: A data structure for retrieval on composite keys. Acta Inf., 4:1–9.
5 Montero-Manso, P. and Hyndman, R. J. (2021). Principles and algorithms for forecasting groups of time series: Locality and globality. International Journal of Forecasting, 37(4):1632–1653.
6 Mueen, A. and Keogh, E. J. (2016). Extracting optimal performance from dynamic time warping. In Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), pages 2129–2130. ACM.
7 Tavenard, R., Faouzi, J., Vandewiele, G., Divo, F., Androz, G., Holtz, C., Payne, M., Yurchak, R., Rußwurm, M., Kolar, K., and Woods, E. (2020). Tslearn, a machine learning toolkit for time series data. Journal of Machine Learning Research, 21(118):1–6.
8 Warren Liao, T. (2005). Clustering of time series data—a survey. Pattern Recognition, 38(11):1857–1874.
9 Vítor Ribeiro, Eduardo H. M. Pena, Raphael de Freitas Saldanha, Reza Akbarinia, Patrick Valduriez, Falaah Arif Khan, Julia Stoyanovich, Fábio Porto: Subset Modelling: A Domain Partitioning Strategy for Data-efficient Machine-Learning. SBBD 2023: 318-323