Machine learning for time series: from forecasting to causal inference
Author:
Affiliation:
1. Computer Science Dept. / Machine Learning Group, Université, Libre de Bruxelles, Belgium
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3549737.3549743
Reference7 articles.
1. S. Ben Taieb , G. Bontempi , A. Sorjamaa , and A. Lendasse . 2009. Long-Term Prediction of Time Series by combining Direct and MIMO Strategies . In Proceedings of the 2009 IEEE International Joint Conference on Neural Networks . Atlanta, U.S.A., 3054–3061. S. Ben Taieb, G. Bontempi, A. Sorjamaa, and A. Lendasse. 2009. Long-Term Prediction of Time Series by combining Direct and MIMO Strategies. In Proceedings of the 2009 IEEE International Joint Conference on Neural Networks. Atlanta, U.S.A., 3054–3061.
2. Multiple-output modeling for multi-step-ahead time series forecasting
3. Learning causal dependencies in large-variate time series
4. G. Bontempi and S. Ben Taieb. 2011. Conditionally dependent strategies for multiple-step-ahead prediction in local learning. International Journal of Forecasting(2011). G. Bontempi and S. Ben Taieb. 2011. Conditionally dependent strategies for multiple-step-ahead prediction in local learning. International Journal of Forecasting(2011).
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