M. Jeroen Van Der Donckt - researchr alias

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Viewing Publication 1 - 8 from 8

2023

Do not sleep on traditional machine learning: Simple and interpretable techniques are competitive to deep learning for sleep scoringM. Jeroen Van Der Donckt, Jonas Van Der Donckt, Emiel Deprost, Nicolas Vandenbussche, Michaël Rademaker, Gilles Vandewiele, Sofie Van Hoecke. bspc, 81:104429, March 2023. [doi]

2022

tsflex: Flexible time series processing & feature extractionJonas Van Der Donckt, M. Jeroen Van Der Donckt, Emiel Deprost, Sofie Van Hoecke. softx, 17:100971, 2022. [doi]

Data Analytics for Health and Connected Care: Ontology, Knowledge Graph and ApplicationsBram Steenwinckel, Mathias De Brouwer, Marija Stojchevska, M. Jeroen Van Der Donckt, Jelle Nelis, Joeri Ruyssinck, Joachim van der Herten, Koen Casier, Jan Van Ooteghem, Pieter Crombez, Filip De Turck, Sofie Van Hoecke, Femke Ongenae. ph 2023: 344-360 [doi]

Powershap: A Power-Full Shapley Feature Selection MethodJarne Verhaeghe, M. Jeroen Van Der Donckt, Femke Ongenae, Sofie Van Hoecke. pkdd 2023: 71-87 [doi]

Deep Learning for Effective and Efficient Reduction of Large Adaptation Spaces in Self-adaptive SystemsDanny Weyns, Omid Gheibi, Federico Quin, M. Jeroen Van Der Donckt. taas, 17, 2022. [doi]

2020

Applying deep learning to reduce large adaptation spaces of self-adaptive systems with multiple types of goalsM. Jeroen Van Der Donckt, Danny Weyns, Federico Quin, Jonas Van Der Donckt, Sam Michiels. ICSE 2020: 20-30 [doi]

2018

Effective Decision Making in Self-adaptive Systems Using Cost-Benefit Analysis at Runtime and Online Learning of Adaptation SpacesM. Jeroen Van Der Donckt, Danny Weyns, M. Usman Iftikhar, Sarpreet Singh Buttar. ENASE 2019: 373-403 [doi]

Cost-Benefit Analysis at Runtime for Self-adaptive Systems Applied to an Internet of Things ApplicationM. Jeroen Van Der Donckt, Danny Weyns, M. Usman Iftikhar, Ritesh Kumar Singh. ENASE 2018: 478-490 [doi]

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