| Machine learning strategies for time series forecasting G Bontempi, S Ben Taieb, YA Le Borgne Business Intelligence, 62-77, 2013 | 534 | 2013 |
| A review and comparison of strategies for multi-step ahead time series forecasting based on the NN5 forecasting competition S Ben Taieb, G Bontempi, AF Atiya, A Sorjamaa Expert systems with applications 39 (8), 7067-7083, 2012 | 503 | 2012 |
| A gradient boosting approach to the Kaggle load forecasting competition S Ben Taieb, RJ Hyndman International journal of forecasting 30 (2), 382-394, 2014 | 269 | 2014 |
| Multiple-output modeling for multi-step-ahead time series forecasting S Ben Taieb, A Sorjamaa, G Bontempi Neurocomputing 73 (10), 1950-1957, 2010 | 201 | 2010 |
| Forecasting uncertainty in electricity smart meter data by boosting additive quantile regression SB Taieb, R Huser, RJ Hyndman, MG Genton IEEE Transactions on Smart Grid 7 (5), 2448-2455, 2016 | 178 | 2016 |
| A Bias and Variance Analysis for Multistep-Ahead Time Series Forecasting S Ben Taieb, AF Atiya IEEE Transactions on Neural Networks and Learning Systems 27 (1), 62-76, 2015 | 122 | 2015 |
| Long-term prediction of time series by combining direct and mimo strategies SB Taieb, G Bontempi, A Sorjamaa, A Lendasse 2009 International Joint Conference on Neural Networks, 3054-3061, 2009 | 84 | 2009 |
| Forecasting: theory and practice F Petropoulos, D Apiletti, V Assimakopoulos, MZ Babai, DK Barrow, ... International Journal of Forecasting, 2022 | 76 | 2022 |
| Conditionally dependent strategies for multiple-step-ahead prediction in local learning G Bontempi, S Ben Taieb International journal of forecasting 27 (3), 689-699, 2011 | 74 | 2011 |
| Coherent probabilistic forecasts for hierarchical time series SB Taieb, JW Taylor, RJ Hyndman International conference on machine learning, 3348-3357, 2017 | 68 | 2017 |
| Hierarchical probabilistic forecasting of electricity demand with smart meter data SB Taieb, JW Taylor, RJ Hyndman Journal of the American Statistical Association 116 (533), 27-43, 2021 | 65 | 2021 |
| Recursive and direct multi-step forecasting: the best of both worlds S Ben Taieb, RJ Hyndman Wroking paper, 2012 | 56* | 2012 |
| Boosting multi-step autoregressive forecasts SB Taieb, R Hyndman International conference on machine learning, 109-117, 2014 | 43 | 2014 |
| Machine learning strategies for multi-step-ahead time series forecasting S Ben Taieb Université Libre de Bruxelles, 2014 | 34* | 2014 |
| Regularization in hierarchical time series forecasting with application to electricity smart meter data SB Taieb, J Yu, M Barreto, R Rajagopal Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017 | 32 | 2017 |
| A time series approach for profiling attack L Lerman, G Bontempi, S Ben Taieb, O Markowitch Security, Privacy, and Applied Cryptography Engineering, 75-94, 2013 | 26 | 2013 |
| Statistical foundations of machine learning G Bontempi, S Ben Taieb Université Libre de Bruxelles: Bruxelles, Belgium, 2008 | 26 | 2008 |
| Adaptive local learning techniques for multiple-step-ahead wind speed forecasting A Vaccaro, G Bontempi, S Ben Taieb, D Villacci Electric power systems research 83 (1), 129-135, 2012 | 24 | 2012 |
| Regularized regression for hierarchical forecasting without unbiasedness conditions S Ben Taieb, B Koo Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019 | 18 | 2019 |
| Recursive multi-step time series forecasting by perturbing data SB Taieb, G Bontempi 2011 IEEE 11th International Conference on Data Mining, 695-704, 2011 | 16 | 2011 |
Gianluca BontempiUniversité Libre de BruxellesVerified email at ulb.ac.be
