Gianluca Bontempi
ABSTRACT
No abstract available.
- 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.Google Scholar
- S. Ben Taieb, A. Sorjamaa, and G. Bontempi. 2010. Multiple-Output Modelling for Multi-Step-Ahead Forecasting. Neurocomputing 73(2010), 1950–1957.Google ScholarDigital Library
- Gianluca Bontempi. 2020. Learning causal dependencies in large-variate time series. In 2020 International Joint Conference on Neural Networks (IJCNN). 1–7. https://doi.org/10.1109/IJCNN48605.2020.9206738Google ScholarCross Ref
- G. Bontempi and S. Ben Taieb. 2011. Conditionally dependent strategies for multiple-step-ahead prediction in local learning. International Journal of Forecasting(2011).Google Scholar
- Gianluca Bontempi and Maxime Flauder. 2015. From Dependency to Causality: A Machine Learning Approach. Journal of Machine Learning Research 16 (2015), 2437–2457. http://jmlr.org/papers/v16/bontempi15a.htmlGoogle ScholarDigital Library
- Gianluca Bontempi, Yann-Aël Le Borgne, and Jacopo De Stefani. 2017. A dynamic factor machine learning method for multi-variate and multi-step-ahead forecasting. In 2017 IEEE International Conference on Data Science and Advanced Analytics (DSAA). IEEE, 222–231.Google ScholarCross Ref
- Jacopo De Stefani and Gianluca Bontempi. 2021. Factor-based framework for multivariate and multi-step-ahead forecasting of large scale time series. Frontiers in Big Data(2021), 75.Google Scholar
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