Souhaib Ben Taieb

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Gianluca BontempiFull professor, Machine Learning Group, Université Libre de BruxellesVerified email at ulb.ac.be
Rob J HyndmanProfessor of Statistics, Monash UniversityVerified email at monash.edu
Amir AtiyaCairo UniversityVerified email at alumni.caltech.edu
James W TaylorProfessor of Decision Science, Said Business School, University of OxfordVerified email at sbs.ox.ac.uk
Yann-Aël Le BorgnePostDoc Researcher, Université Libre de Bruxelles, BelgiumVerified email at ulb.ac.be
Marc G GentonAl-Khawarizmi Distinguished Professor of Statistics, KAUSTVerified email at kaust.edu.sa
Raphaël HuserAssociate Professor, King Abdullah University of Science and Technology (KAUST)Verified email at kaust.edu.sa
Amaury LendasseUniversity of HoustonVerified email at central.uh.edu
Bonsoo KooMonash UniversityVerified email at monash.edu
Victor DheurPhD student, University of Mons, BelgiumVerified email at umons.ac.be
Ram RajagopalAssociate Professor, Stanford UniversityVerified email at stanford.edu
Jiafan YuWaymo LLCVerified email at waymo.com
Tanguy BosserPhD candidate, University of MonsVerified email at umons.ac.be
Alfredo VaccaroUniversità degli studi del SannioVerified email at unisannio.it
Liran LermanUniversité libre de BruxellesVerified email at lerman.be
Olivier MarkowitchUniversité Libre de Bruxelles, BelgiumVerified email at ulb.be
Don VicendeseResearch FellowVerified email at unimelb.edu.au
Jeff S. ShammaDepartment Head, Industrial and Systems Engineering, University of Illinois at Urbana ChampaignVerified email at illinois.edu
Christian ClaudelUT AustinVerified email at utexas.edu
Xiaochun MengSenior Lecturer (Associate Professor) in Finance, University of BathVerified email at bath.ac.uk

Souhaib Ben Taieb

MBZUAI, UMONS

Verified email at mbzuai.ac.ae - Homepage

Artificial intelligence Machine learning Statistics Forecasting Time series


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Machine learning strategies for time series forecasting G Bontempi, S Ben Taieb, YA Le Borgne Business Intelligence, 62-77, 2013	835	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	779	2012
Forecasting: theory and practice F Petropoulos, D Apiletti, V Assimakopoulos, MZ Babai, DK Barrow, ... International Journal of Forecasting 38 (3), 705-871, 2022	737	2022
A gradient boosting approach to the Kaggle load forecasting competition S Ben Taieb, RJ Hyndman International journal of forecasting 30 (2), 382-394, 2014	355	2014
Multiple-output modeling for multi-step-ahead time series forecasting S Ben Taieb, A Sorjamaa, G Bontempi Neurocomputing 73 (10), 1950-1957, 2010	289	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	233	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	201	2015
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	148	2021
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	121	2009
Recursive and direct multi-step forecasting: the best of both worlds S Ben Taieb, RJ Hyndman Wroking paper, 2012	112*	2012
Coherent probabilistic forecasts for hierarchical time series SB Taieb, JW Taylor, RJ Hyndman International Conference on Machine Learning, 3348-3357, 2017	110	2017
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	98	2011
Regularized regression for hierarchical forecasting without unbiasedness conditions S Ben Taieb, B Koo Proceedings of the 25th ACM SIGKDD international conference on knowledge …, 2019	60	2019
Boosting multi-step autoregressive forecasts SB Taieb, R Hyndman International conference on machine learning, 109-117, 2014	56	2014
Machine learning strategies for multi-step-ahead time series forecasting S Ben Taieb Université Libre de Bruxelles, 2014	46*	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	40	2017
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	29	2012
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	28	2013
Recursive multi-step time series forecasting by perturbing data SB Taieb, G Bontempi 2011 IEEE 11th International Conference on Data Mining, 695-704, 2011	28	2011
Hospital characteristics, rather than surgical volume, predict length of stay following colorectal cancer surgery D Vicendese, L Te Marvelde, PD McNair, K Whitfield, DR English, ... Australian and New Zealand journal of public health 44 (1), 73-82, 2020	16	2020

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