Publications


2017

  • Hierarchical Probabilistic Forecasting of Electricity Demand with Smart Meter Data
    Souhaib Ben Taieb, James W. Taylor and Rob J. Hyndman
    Submitted.
    [pdf]

  • Coherent Probabilistic Forecasts for Hierarchical Time Series
    Souhaib Ben Taieb, James W. Taylor and Rob J. Hyndman
    Proceedings of the 34 st International Conference on Machine Learning (ICML), PMLR 70, 2017.
    [pdf]

  • Sparse and Smooth Adjustments for Coherent Forecasts in Temporal Aggregation of Time Series
    Souhaib Ben Taieb
    NIPS 2016 Time Series Workshop, JMLR W&CP Vol. 55, 2017
    [pdf]

  • Regularization in Hierarchical Time Series Forecasting With Application to Electricity Smart Meter Data
    Souhaib Ben Taieb, Jiafan Yu, Mateus Neves Barreto and Ram Rajagopal
    Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence. AAAI Press, 2017.
    [pdf]

2016

  • Forecasting Uncertainty in Electricity Smart Meter Data by Boosting Additive Quantile Regression
    Souhaib Ben Taieb, Raphael Huser, Rob J. Hyndman and Marc G. Genton
    IEEE Transactions on Smart Grid, vol. 7, no. 5, pp. 2448-2455, Sept. 2016.
    [pdf] [link] [seminar link]

  • A Bias and Variance Analysis for Multistep-Ahead Time Series Forecasting
    Souhaib Ben Taieb and Amir F. Atiya
    IEEE Transactions on Neural Networks and Learning Systems, vol. 27, no. 1, pp. 62-76, 2016.
    [pdf] [link]

2015 & 2014

  • Machine learning strategies for multi-step-ahead time series forecasting
    Souhaib Ben Taieb
    PhD thesis.
    [pdf]

  • Boosting multi-step autoregressive forecasts
    Souhaib Ben Taieb and Rob J. Hyndman
    Proceedings of the 31 st International Conference on Machine Learning (ICML), JMLR: W&CP volume 32, 2014.
    [pdf]

  • A gradient boosting approach to the Kaggle load forecasting competition
    Souhaib Ben Taieb and Rob J. Hyndman
    International Journal of Forecasting, Volume 30, Issue 2, 2014.
    [pdf] [link]

2013

  • A Time Series Approach for Profiling Attack
    Liran Lerman, Gianluca Bontempi, Souhaib Ben Taieb and Olivier Markowitch
    Lecture Notes in Computer Science, Volume 8204, 75-94, 2013
    [link]

  • Machine Learning Strategies for Time Series Forecasting
    Gianluca Bontempi, Souhaib Ben Taieb and Y.-A. Le Borgne
    Business Intelligence, Vol. 138. Springer, pp.62–77, 2013.
    [link]

2012

  • A review and comparison of strategies for multi-step ahead time series forecasting based on the NN5 forecasting competition
    Souhaib Ben Taieb, Gianluca Bontempi, Amir F. Atiya and Antti Sorjamaa
    Expert Systems with Applications, 39(8):7067–7083, 2012.
    [pdf]

  • Adaptive local learning techniques for multiple-step-ahead wind speed forecasting
    Alfredo Vaccaro, Gianluca Bontempi, Souhaib Ben Taieb and Domenico Villacci
    Electric Power Systems Research, 83(1):129–135, 2012.
    [link]

2011

  • Conditionally dependent strategies for multiple-step-ahead prediction in local learning
    Gianluca Bontempi and Souhaib Ben Taieb
    International Journal of Forecasting, 27(3):689–699, 2011.
    [pdf]

  • Recursive Multi-step Time Series Forecasting by Perturbing Data
    Souhaib Ben Taieb and Gianluca Bontempi
    IEEE International Conference on Data Mining (ICDM), December, 2011.
    [pdf]

2010

  • Multiple-output modeling for multi-step-ahead time series forecasting
    Souhaib Ben Taieb, Antti Sorjamaa and Gianluca Bontempi
    Neurocomputing, 73(10-12):1950–1957, 2010.
    [pdf]

2009

  • Long-Term Prediction of Time Series by combining Direct and MIMO Strategies
    Souhaib Ben Taieb, Gianluca Bontempi, Antti Sorjamaa and Amaury Lendasse
    IEEE International Joint Conference on Neural Networks (IJCNN), 2009.
    [pdf]