Research Unit Knowledge-based Systems
Mathematical and Computational Modelling in the Information Age
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2016 (2)
2015 (1)
2014 (4)
2013 (7)
2012 (6)
2011 (6)
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2007 (1)
(2)
Kernel-based learning methods for preference aggregation
W. Waegeman, B. De Baets and L. Boullart(2009) 4OR. 7, 169-189.
(1)
Learning to Rank: a ROC-based Graph-Theoretic Approach
W. Waegeman(2009) 4OR. 7, 399-402.
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2022 (1)
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2016 (2)
2015 (1)
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2012 (4)
2011 (6)
2010 (8)
2009 (4)
2008 (2)
2007 (2)
2006 (2)
2023 (1)
(4)
Learning Partial Class Memberships in Multi-Class Classification Problems: a Probabilistic Approach
W. Waegeman and B. De Baets(2009) EUROFUSE WORKSHOP ON PREFERENCE HANDLING AND DECISION SUPPORT.Pamplona, Spain, 6 pages. .
(3)
A Comparison of AUC Estimators in Small-Sample Studies
A. Airola, T. Pahikkala, W. Waegeman, B. De Baets and T. Salakoski(2009) 3RD WORKSHOP ON MACHINE LEARNING IN SYSTEMS BIOLOGY.Ljubljana, Slovenia, 3-13. MLR Workshop and Conference Proceedings 8.
(2)
From Ranking to Intransitive Preference Learning: Rock-Paper-Scissors and Beyond
T. Pahikkala, W. Waegeman, E. Tsivtsivadze, T. Salakoski and B. De Baets(2009) ECML 2009 WORKSHOP ON PREFERENCE LEARNING.Bled, Slovenia, 16 pages. .
(1)
Learning Intransitive Reciprocal Relations with Regularized Least-Squares
T. Pahikkala, W. Waegeman, E. Tsivtsivadze, T. Salakoski and B. De Baets(2009) BENELEARN 2008 BENELUX CONFERENCE ON MACHINE LEARNING.Tilburg, The Netherlands, 8 pages. .
Editor
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Awards
Date
Title
W. Waegeman
18/08/2014
2015 IEEE CIS Outstanding TFS Paper Award
27/08/2012
Best Paper Award for Willem Waegeman
17/08/2012
Second Winner Award for Willem Waegeman
Students
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MSc
PhD Students
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MSc Students
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Graduates
Phd
MSc
PhD Students
Name
Title
Date
N. Dewolf
A comparative study of conformal prediction methods for valid uncertainty quantification in machine learning
25/04/2024
D. Iliadis
Automated multi-target prediction with two-branch neural networks
17/11/2023
T. Mortier
Efficient algorithms for set-valued prediction in classification
23/06/2023
M. Gasparyan
Model reduction and parameter estimation for kinetic models of biochemical reaction networks
19/01/2023
F. Mey
Integration of synthetic biology, systems biology and machine learning for the production of chitooligosaccharides in Escherichia coli
18/01/2023
J. Clauwaert
Deep learning techniques for genome processing and annotation tasks in prokaryotes
24/09/2020
P. Rubbens
Machine learning approaches for microbial flow cytometry at the single-cell and community level
24/09/2019
C. Papagiannopoulou
A data-guided insight into global climate-vegetation dynamics
05/10/2018
M. Stock
Exact and efficient algorithms for pairwise learning
21/04/2017
MSc Students
Name
Title
Date
N. Tourne
Two-branch neural networks for predicting protein-DNA interaction
2022 - 2023
J.-H. Nowé
Countering illegal timbering by using multimodal machine learning
2022 - 2023
Y. Van Laere
Detection of 5mC modification in Nanopore sequencing data using deep learning
2021 - 2022
E. Lorrez
Quantifying the environmental controls on African tropical forest dynamics through using a Granger causality framework
2020 - 2021
K. Zhang
Drug-target interaction prediction using multi-target prediction methods
2020 - 2021
L. Theunissen
A comparison of flat and hierarchical classification for automatic annotation of single-cell transcriptomics data
2020 - 2021
T. Willaert
Improving classification by rejection of high epistemic uncertainty points
2020 - 2021
L. Pollaris
Protein secondary structure prediction using transformer networks
2019 - 2020
B. De Saedeleer
Combatting illegal timber trade using chemical fingerprints: the power of mathematics and mass spectrometry
2019 - 2020
B. Verfaillie
Pattern recognition in raman spectroscopy data for a faster labelling of subjects in multiple domains
2019 - 2020
L. Davey
Using artificial neural networks to uncover features in promoter sequences responsible for nonorthogonality in E. Coli
2019 - 2020
G. Tjon
Automative drinking water monitoring using flow cytometry data
2019 - 2020
S. Top
Vertical farming of lettuce: the influence of rhizosphere bacteria and substrates
2018 - 2019
K. D'haeyer
Towards a data-driven identification of the microbial "Rammanome"
2018 - 2019
G. De Clercq
Deep learning for classification of DNA functional sequences
2018 - 2019
N. Goeders
Fight the illegal wood trade through chemical fingerprints : The power of mathematics and mass spectrometry
2018 - 2019
B. De Clercq
Forecasting tidal surge in the Lower Sea Scheldt using machine learning techniques
2018 - 2019
M. Van Haeverbeke
Detection of m6a modifications in native RNA using Oxford Nanopore Technology
2018 - 2019
M. Misonne
Prediction of RNA polymerase-DNA interactions in Escherichia Coli
2017 - 2018
R. Ingels
Understanding vegetation anomalies with machine learning methods
2017 - 2018
A. De Graeve
Detecting climate drivers for vegetation extremes
2017 - 2018
T. Vanlerberghe
Hierarchical multi-label classification of food products
2017 - 2018
T. Mortier
Modeling of climate-vegetation dynamics using machine learning techniques in a non-linear Granger causality framework
2016 - 2017
X. Yin
Discovering relationships in climate-vegetation dynamics using dynamic feature selection techniques
2016 - 2017
D. Schaumont
Een integratieve benadering gebaseerd op random forest voor de verbeterde predictie van exon-intron juncties
2016 - 2017
C. Zhang
Visualization and unsupervised learning of flow cytometry data for bacterial identication
2016 - 2017
S. Decubber
Spatiotemporal optimization of Granger causality methods for climate change attribution
2016 - 2017
J. Heyse
Development and application of single-cell analysis tools for the study of sympatric bacterial populations
2016 - 2017
L. Bodyn
Exploration of deep autoencoders for collaborative filtering on cooking recipes
2016 - 2017
L. Tilleman
In silico engineering van cytochroom P450 via machine learning technieken
2015 - 2016
F. Ramon
A data-driven analysis of ingredients in cooking recipes
2015 - 2016
W.K. Tsang
Assessing pathogen invasion based on community evenness and metabolic similarity
2014 - 2015
J. De Reu
Analyse van voorspellingsmodellen voor aardappelziekten en hun toepasbaarheid in Vlaanderen
2014 - 2015
M. De Clercq
Prediction of ingredient combinations using machine learning techniques
2013 - 2014
A. De Paepe
The prediction of interaction between mRNA and miRNA using machine learning techniques
2012 - 2013
M. Stock
Learning pairwise relations in bioinformatics: three case studies
2011 - 2012
J. Vandepitte
Voorspellen van Fusarium spp. aanwezigheid en DON concentraties in wintertarwe met machine learning technieken
2009 - 2010