Dumas, J., Wehenkel, A., Lanaspeze, D., Cornélusse, B., & Sutera, A. (01 January 2022). A deep generative model for probabilistic energy forecasting in power systems: normalizing flows. Applied Energy, 305, 117-871. doi:10.1016/j.apenergy.2021.117871
Greater direct electrification of end-use sectors with a higher share of renewables is one of the...
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Schumacher, P., & Sutera, A. (2022). Analyse comparative de post-édition et de traduction humaine en contexte académique. In C. Expósito Castro, M. D. M. Ogea Pozo, ... F. Rodríguez Rodríguez, Theory and practice of translation as a vehicle for knowledge transfer (pp. 173-208). Séville, Spain: Editorial Universidad de Sevilla.
La traduction automatique (TA) neuronale bouleverse aujourd’hui le secteur des services langagier...
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Sutera, A., Louppe, G., Huynh-Thu, V. A., Wehenkel, L., & Geurts, P. (2021). From global to local MDI variable importances for random forests and when they are Shapley values. Advances in Neural Information Processing Systems.
Random forests have been widely used for their ability to provide so-called importance measures, ...
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Dumas, J., Cointe, C., Wehenkel, A., Sutera, A., Fettweis, X., & Cornélusse, B. (2021). A Probabilistic Forecast-Driven Strategy for a Risk-Aware Participation in the Capacity Firming Market. IEEE Transactions on Sustainable Energy. doi:10.1109/TSTE.2021.3117594
This paper addresses the energy management of a grid-connected renewable generation plant coupled...
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Marulli, D., Mathieu, S., Benzerga, A., Sutera, A., & Ernst, D. (2021). Reconstruction of low-voltage networks with limited observability. In IEEE PES Innovative Smart Grid Technologies Conference Europe. doi:10.1109/ISGTEurope52324.2021.9640163
This work addresses the problem of reconstructing topology and cable parameters of thr...
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Benzerga, A., Maruli, D., Sutera, A., Bahmanyar, A., Mathieu, S., & Ernst, D. (2021). Low-voltage network topology and impedance identification using smart meter measurements. In Proceedings of the 2021 IEEE Madrid PowerTech. doi:10.1109/PowerTech46648.2021.9495093
Distribution system operators have been upgrading their network over several decades, though not ...
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Duchesne, L., Karangelos, E., Sutera, A., & Wehenkel, L. (2020). Machine Learning for Ranking Day-ahead Decisions in the Context of Short-term Operation Planning. Electric Power Systems Research. doi:10.1016/j.epsr.2020.106548
In operation planning, probabilistic reliability assessment consists in evaluating, for various c...
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Vecoven, N., Begon, J.-M., Sutera, A., Geurts, P., & Huynh-Thu, V. A. (2020). Nets versus trees for feature ranking and gene network inference. In Proceeding of the 23rd International Conference on Discovery Science (DS 2020). Springer. doi:10.1007/978-3-030-61527-7_16
We investigate several global variable importance measures derived from artificial neural network...
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Sutera, A. (2019). Importance measures derived from random forests: characterisation and extension [Doctoral thesis, ULiège - Université de Liège]. ORBi-University of Liège. https://orbi.uliege.be/handle/2268/236868
Nowadays new technologies, and especially artificial intelligence, are more and more established...
Sutera, A. (2019). Lecture on "Variable selection using random forests" (R. Genuer et al., 2010). (ULiège - Université de Liège, INFO8004 - Advanced Machine Learning).
Wehenkel, M., Sutera, A., Bastin, C., Geurts, P.* , & Phillips, C.*. (29 June 2018). Random Forests based group importance scores and their statistical interpretation: application for Alzheimer’s disease. Frontiers in Neuroscience, 12, 411. doi:10.3389/fnins.2018.00411
Machine learning approaches have been increasingly used in the neuroimaging field for the design ...
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Olivier, F., Sutera, A., Geurts, P., Fonteneau, R., & Ernst, D. (2018). Phase Identification of Smart Meters by Clustering Voltage Measurements. In Proceedings of the XX Power Systems Computation Conference (PSCC 2018). doi:10.23919/PSCC.2018.8442853
When a smart meter, be it single-phase or threephase, is connected to a three-phase network, the ...
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Sutera, A., Châtel, C., Louppe, G., Wehenkel, L., & Geurts, P. (2018). Random Subspace with Trees for Feature Selection Under Memory Constraints. In A. Storkey & F. Perez-Cruz (Eds.), Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics (pp. 929-937). Playa Blanca, Spain: PMLR.
Dealing with datasets of very high dimension is a major challenge in machine learning. In this pa...
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Sutera, A., Joly, A., François-Lavet, V., Qiu, Z., Ernst, D., & Geurts, P. (2017). Simple connectome inference from partial correlation statistics in calcium imaging. In J. Soriano, D. Battaglia, I. Guyon, V. Lemaire, J. Orlandi, ... B. Ray (Eds.), Neural Connectomics Challenge (pp. 23-36). Springer. doi:10.1007/978-3-319-53070-3
In this work, we propose a simple yet effective solution to the problem of connectome inference i...
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Sutera, A., Châtel, C., Louppe, G., Wehenkel, L., & Geurts, P. (12 September 2016). Random subspace with trees for feature selection under memory constraints [Poster presentation]. The 25th Belgian-Dutch Conference on Machine Learning (Benelearn), Kortrijk, Belgium.
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Sutera, A. (24 August 2016). Random forests variable importances Towards a better understanding and large-scale feature selection [Paper presentation]. 22nd International Conference on Computational Statistics (COMPSTAT 2016), Oviedo, Spain.
Sutera, A., Louppe, G., Huynh-Thu, V. A., Wehenkel, L., & Geurts, P. (2016). Context-dependent feature analysis with random forests. In Uncertainty In Artificial Intelligence: Proceedings of the Thirty-Two Conference (2016).
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Taralla, D., Qiu, Z., Sutera, A., Fonteneau, R., & Ernst, D. (2016). Decision Making from Confidence Measurement on the Reward Growth using Supervised Learning: A Study Intended for Large-Scale Video Games. In Proceedings of the 8th International Conference on Agents and Artificial Intelligence (ICAART 2016) - Volume 2 (pp. 264-271). doi:10.5220/0005666202640271
Video games have become more and more complex over the past decades. Today, players wander in vis...
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Sutera, A., Joly, A., François-Lavet, V., Qiu, Z., Louppe, G., Ernst, D., & Geurts, P. (2014). Simple connectome inference from partial correlation statistics in calcium imaging. In J. Soriano, D. Battaglia, I. Guyon, V. Lemaire, J. Orlandi, ... B. Ray (Eds.), Neural Connectomics Challenge. Springer.
In this work, we propose a simple yet effective solution to the problem of connectome inference i...
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Louppe, G., Wehenkel, L., Sutera, A., & Geurts, P. (2013). Understanding variable importances in forests of randomized trees. In Advances in Neural Information Processing Systems 26.
Despite growing interest and practical use in various scientific areas, variable importances deri...
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Sutera, A. (2013). Characterization of variable importance measures derived from decision trees [Master’s dissertation, ULiège - Université de Liège]. ORBi-University of Liège. https://orbi.uliege.be/handle/2268/157155
In the context of machine learning, tree-based ensemble methods are common techniques used for pr...