M. Jeroen Van Der Donckt

Orcid: 0000-0002-9620-888X

According to our database1, M. Jeroen Van Der Donckt authored at least 13 papers between 2018 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Bibliography

2023
Do not sleep on traditional machine learning: Simple and interpretable techniques are competitive to deep learning for sleep scoring.
Biomed. Signal Process. Control., March, 2023

tsdownsample: high-performance time series downsampling for scalable visualization.
CoRR, 2023

MinMaxLTTB: Leveraging MinMax-Preselection to Scale LTTB.
CoRR, 2023

Data Point Selection for Line Chart Visualization: Methodological Assessment and Evidence-Based Guidelines.
CoRR, 2023

2022
Deep Learning for Effective and Efficient Reduction of Large Adaptation Spaces in Self-adaptive Systems.
ACM Trans. Auton. Adapt. Syst., 2022

tsflex: Flexible time series processing & feature extraction.
SoftwareX, 2022

Do Not Sleep on Linear Models: Simple and Interpretable Techniques Outperform Deep Learning for Sleep Scoring.
CoRR, 2022

Plotly-Resampler: Effective Visual Analytics for Large Time Series.
CoRR, 2022

Powershap: A Power-Full Shapley Feature Selection Method.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

Data Analytics for Health and Connected Care: Ontology, Knowledge Graph and Applications.
Proceedings of the Pervasive Computing Technologies for Healthcare, 2022

2020
Applying deep learning to reduce large adaptation spaces of self-adaptive systems with multiple types of goals.
Proceedings of the SEAMS '20: IEEE/ACM 15th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, Seoul, Republic of Korea, 29 June, 2020

2018
Cost-Benefit Analysis at Runtime for Self-adaptive Systems Applied to an Internet of Things Application.
Proceedings of the 13th International Conference on Evaluation of Novel Approaches to Software Engineering, 2018

Effective Decision Making in Self-adaptive Systems Using Cost-Benefit Analysis at Runtime and Online Learning of Adaptation Spaces.
Proceedings of the Evaluation of Novel Approaches to Software Engineering, 2018


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