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Trabalho de evento
On the effect of endpoints on dynamic time warping (2016)
Silva, Diego Furtado ; Batista, Gustavo Enrique de Almeida Prado Alves; Keogh, Eamonn
Source: Proceedings. Conference titles: SIGKDD Workshop on Mining and Learning from Time Series - SIGKDD MiLeTS. Unidade: ICMC
Subjects: INTELIGÊNCIA ARTIFICIAL, MINERAÇÃO DE DADOS, ANÁLISE DE SÉRIES TEMPORAIS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SILVA, Diego Furtado e BATISTA, Gustavo Enrique de Almeida Prado Alves e KEOGH, Eamonn. On the effect of endpoints on dynamic time warping. 2016, Anais.. New York: ACM, 2016. Disponível em: https://doi.org/10.1145/12345.67890. Acesso em: 16 nov. 2024.
APA
Silva, D. F., Batista, G. E. de A. P. A., & Keogh, E. (2016). On the effect of endpoints on dynamic time warping. In Proceedings. New York: ACM. doi:10.1145/12345.67890
NLM
Silva DF, Batista GE de APA, Keogh E. On the effect of endpoints on dynamic time warping [Internet]. Proceedings. 2016 ;[citado 2024 nov. 16 ] Available from: https://doi.org/10.1145/12345.67890
Vancouver
Silva DF, Batista GE de APA, Keogh E. On the effect of endpoints on dynamic time warping [Internet]. Proceedings. 2016 ;[citado 2024 nov. 16 ] Available from: https://doi.org/10.1145/12345.67890
Trabalho de evento
DTW-D: time series semi-supervised learning from a single example (2013)
Chen, Yanping; Hu, Bing; Keogh, Eamonn; Batista, Gustavo Enrique de Almeida Prado Alves
Source: Proceedings. Conference titles: ACM SIGKDD International Conference on Knowledge Discovery and Data Mining - KDD. Unidade: ICMC
Assunto: INTELIGÊNCIA ARTIFICIAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CHEN, Yanping et al. DTW-D: time series semi-supervised learning from a single example. 2013, Anais.. New York: ACM, 2013. Disponível em: https://doi.org/10.1145/2487575.2487633. Acesso em: 16 nov. 2024.
APA
Chen, Y., Hu, B., Keogh, E., & Batista, G. E. de A. P. A. (2013). DTW-D: time series semi-supervised learning from a single example. In Proceedings. New York: ACM. doi:10.1145/2487575.2487633
NLM
Chen Y, Hu B, Keogh E, Batista GE de APA. DTW-D: time series semi-supervised learning from a single example [Internet]. Proceedings. 2013 ;[citado 2024 nov. 16 ] Available from: https://doi.org/10.1145/2487575.2487633
Vancouver
Chen Y, Hu B, Keogh E, Batista GE de APA. DTW-D: time series semi-supervised learning from a single example [Internet]. Proceedings. 2013 ;[citado 2024 nov. 16 ] Available from: https://doi.org/10.1145/2487575.2487633
Trabalho de evento
Searching and mining trillions of time series subsequences under dynamic time warping (2012)
Rakthanmanon, Thanawin; Campana, Bilson; Mueen, Abdullah; Batista, Gustavo Enrique de Almeida Prado Alves; Westover, Brandon; Qiang, Zhu; Zakaria, Jesin; Keogh, Eamonn
Source: Proceedings. Conference titles: ACM SIGKDD International Conference on Knowledge Discovery and Data Mining - KDD. Unidade: ICMC
Assunto: INTELIGÊNCIA ARTIFICIAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
RAKTHANMANON, Thanawin et al. Searching and mining trillions of time series subsequences under dynamic time warping. 2012, Anais.. New York: ACM, 2012. Disponível em: https://doi.org/10.1145/2339530.2339576. Acesso em: 16 nov. 2024.
APA
Rakthanmanon, T., Campana, B., Mueen, A., Batista, G. E. de A. P. A., Westover, B., Qiang, Z., et al. (2012). Searching and mining trillions of time series subsequences under dynamic time warping. In Proceedings. New York: ACM. doi:10.1145/2339530.2339576
NLM
Rakthanmanon T, Campana B, Mueen A, Batista GE de APA, Westover B, Qiang Z, Zakaria J, Keogh E. Searching and mining trillions of time series subsequences under dynamic time warping [Internet]. Proceedings. 2012 ;[citado 2024 nov. 16 ] Available from: https://doi.org/10.1145/2339530.2339576
Vancouver
Rakthanmanon T, Campana B, Mueen A, Batista GE de APA, Westover B, Qiang Z, Zakaria J, Keogh E. Searching and mining trillions of time series subsequences under dynamic time warping [Internet]. Proceedings. 2012 ;[citado 2024 nov. 16 ] Available from: https://doi.org/10.1145/2339530.2339576
Trabalho de evento
SIGKDD Demo: sensors and software to allow computational entomology, an emerging application of data miming (2011)
Batista, Gustavo Enrique de Almeida Prado Alves; Keogh, Eamonn; Mafra Neto, Agenor; Rowton, Edgar
Source: Proceedings. Conference titles: ACM SIGKDD International Conference on Knowledge Discovery and Data Mining - KDD. Unidade: ICMC
Assunto: INTELIGÊNCIA ARTIFICIAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
BATISTA, Gustavo Enrique de Almeida Prado Alves et al. SIGKDD Demo: sensors and software to allow computational entomology, an emerging application of data miming. 2011, Anais.. New York: ACM, 2011. Disponível em: https://doi.org/10.1145/2020408.2020530. Acesso em: 16 nov. 2024.
APA
Batista, G. E. de A. P. A., Keogh, E., Mafra Neto, A., & Rowton, E. (2011). SIGKDD Demo: sensors and software to allow computational entomology, an emerging application of data miming. In Proceedings. New York: ACM. doi:10.1145/2020408.2020530
NLM
Batista GE de APA, Keogh E, Mafra Neto A, Rowton E. SIGKDD Demo: sensors and software to allow computational entomology, an emerging application of data miming [Internet]. Proceedings. 2011 ;[citado 2024 nov. 16 ] Available from: https://doi.org/10.1145/2020408.2020530
Vancouver
Batista GE de APA, Keogh E, Mafra Neto A, Rowton E. SIGKDD Demo: sensors and software to allow computational entomology, an emerging application of data miming [Internet]. Proceedings. 2011 ;[citado 2024 nov. 16 ] Available from: https://doi.org/10.1145/2020408.2020530

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