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Michaël Rademaker
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2020 – today
- 2023
- [j15]M. Jeroen Van Der Donckt
, Jonas Van Der Donckt
Do not sleep on traditional machine learning: Simple and interpretable techniques are competitive to deep learning for sleep scoring. Biomed. Signal Process. Control. 81: 104429 (2023) - [c7]Jeroen Van Der Donckt, Jonas Van Der Donckt, Michaël Rademaker, Sofie Van Hoecke:
MinMaxLTTB: Leveraging MinMax-Preselection to Scale LTTB. IEEE VIS (Short Papers) 2023: 21-25 - [i3]Jonas Van Der Donckt, M. Jeroen Van Der Donckt, Michaël Rademaker
Data Point Selection for Line Chart Visualization: Methodological Assessment and Evidence-Based Guidelines. CoRR abs/2304.00900 (2023) - [i2]M. Jeroen Van Der Donckt, Jonas Van Der Donckt, Michaël Rademaker
MinMaxLTTB: Leveraging MinMax-Preselection to Scale LTTB. CoRR abs/2305.00332 (2023) - 2022
- [i1]M. Jeroen Van Der Donckt, Jonas Van Der Donckt, Emiel Deprost, Nicolas Vandenbussche, Michaël Rademaker
Do Not Sleep on Linear Models: Simple and Interpretable Techniques Outperform Deep Learning for Sleep Scoring. CoRR abs/2207.07753 (2022) - 2020
- [j14]Ignacio Montes
A correspondence between voting procedures and stochastic orderings. Eur. J. Oper. Res. 285(3): 977-987 (2020)
2010 – 2019
- 2017
- [j13]Raúl Pérez-Fernández
Monotonicity-based ranking on the basis of multiple partially specified reciprocal relations. Fuzzy Sets Syst. 325: 69-96 (2017) - [j12]Raúl Pérez-Fernández
Monometrics and their role in the rationalisation of ranking rules. Inf. Fusion 34: 16-27 (2017) - 2016
- [j11]Raúl Pérez-Fernández
Representations of votes facilitating monotonicity-based ranking rules: From votrix to votex. Int. J. Approx. Reason. 73: 87-107 (2016) - [j10]Raúl Pérez-Fernández
The scorix: A popular representation of votes revisited. Int. J. Approx. Reason. 78: 241-251 (2016) - 2015
- [j9]Jan Verwaeren
An interval estimator for the unmixing of mixtures with set-based source descriptions. Int. J. Approx. Reason. 60: 71-92 (2015) - [c6]Raúl Pérez-Fernández, Michaël Rademaker, Pedro Alonso, Irene Díaz, Bernard De Baets:
Adding feasibility constraints to a ranking rule under a monotonicity constraint. IFSA-EUSFLAT 2015 - 2014
- [j8]Matteo Reggente
Prediction of ultrafine particle number concentrations in urban environments by means of Gaussian process regression based on measurements of oxides of nitrogen. Environ. Model. Softw. 61: 135-150 (2014) - [j7]Michaël Rademaker
A ranking procedure based on a natural monotonicity constraint. Inf. Fusion 17: 74-82 (2014) - 2012
- [j6]Michaël Rademaker
Consistent union and prioritized consistent union: new operations for preference aggregation. Ann. Oper. Res. 195(1): 237-259 (2012) - [j5]Michaël Rademaker
Optimal monotone relabelling of partially non-monotone ordinal data. Optim. Methods Softw. 27(1): 17-31 (2012) - 2011
- [j4]Michaël Rademaker
Aggregation of monotone reciprocal relations with application to group decision making. Fuzzy Sets Syst. 184(1): 29-51 (2011) - [j3]Michaël Rademaker
Optimal restoration of stochastic monotonicity with respect to cumulative label frequency loss functions. Inf. Sci. 181(4): 747-757 (2011) - 2010
- [c5]Michaël Rademaker
A threshold for majority in the context of aggregating partial order relations. FUZZ-IEEE 2010: 1-4 - [c4]Damiano Oldoni
Context-dependent environmental sound monitoring using SOM coupled with LEGION. IJCNN 2010: 1-8 - [c3]Weiwei Cheng, Michaël Rademaker
Predicting Partial Orders: Ranking with Abstention. ECML/PKDD (1) 2010: 215-230
2000 – 2009
- 2009
- [j2]Kamran Zendehdel, Michaël Rademaker
Improving tractability of group decision making on environmental problems through the use of social intensities of preferences. Environ. Model. Softw. 24(12): 1457-1466 (2009) - [j1]Michaël Rademaker
Loss optimal monotone relabeling of noisy multi-criteria data sets. Inf. Sci. 179(24): 4089-4096 (2009) - 2007
- [c2]Michaël Rademaker, Bernard De Baets, Hans E. De Meyer, Rainer Brüggemann:
Directional Adjustment of Average Rankings of Two Posets: an Application to Herb Layer and Moss Layer Pollution in Baden-Württemberg. EnviroInfo (2) 2007: 181-185 - 2006
- [c1]Michaël Rademaker
On the Role of Maximal Independent Sets in Cleaning Data Sets for Supervised Ranking. FUZZ-IEEE 2006: 1619-1624
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