KERMIT -- Research Unit Knowledge-based Systems

Journal papers

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2025 (1)
2024 (3)
2023 (2)
2022 (4)
2021 (12)
2020 (5)
2019 (7)
2018 (7)
2017 (10)
2016 (2)
2015 (1)
2014 (4)
2013 (7)
2012 (6)
2011 (6)
2010 (4)
2009 (2)
2008 (4)
2007 (1)

(6) A kernel-based framework for learning graded relations from data
W. Waegeman, T. Pahikkala, A. Airola, T. Salakoski, M. Stock and B. De Baets
(2012) IEEE TRANSACTIONS ON FUZZY SYSTEMS. 20, 1090-1101.

(5) The logistic curve as a tool to describe the daily ruminal pH pattern and its link with milk fatty acids
E. Colman, B. Thas, W. Waegeman, B. De Baets and V. Fievez
(2012) J. DAIRY SCIENCE. 95, 5845-5865.

(4) On label dependence and loss minimization in multi-label classification
K. Dembczynski, W. Waegeman, W. Cheng and E. Hüllermeier
(2012) MACHINE LEARNING. 88, 5-45.

(3) Towards a reliable evaluation of forecasting systems for plant diseases: A case study of Fusarium head blight
S. Landschoot, W. Waegeman, K. Audenaert, J. Vandepitte, G. Haesaert and B. De Baets
(2012) PLANT DISEASE. 96, 889-896.

(2) An empirical analysis of explanatory variables affecting Fusarium head blight infection and deoxynivalenol content in wheat
S. Landschoot, W. Waegeman, K. Audenaert, J. Vandepitte, J.M. Baetens, B. De Baets and G. Haesaert
(2012) JOURNAL OF PLANT PATHOLOGY. 94, 135-147.

(1) Learning partial ordinal class memberships with kernel-based proportional odds models
J. Verwaeren, W. Waegeman and B. De Baets
(2012) COMPUTATIONAL STATISTICS AND DATA ANALYSIS. 56, 928-942.

Conference papers

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2022 (1)
2019 (1)
2018 (1)
2017 (1)
2016 (2)
2015 (1)
2014 (1)
2013 (1)
2012 (4)
2011 (6)
2010 (8)
2009 (4)
2008 (2)
2007 (2)
2006 (2)
2023 (1)

(4) Label ranking with partial abstention based on thresholded probabilistic models
W. Cheng, E. Hüllermeier , W. Waegeman and V. Welker
(2012) ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS (NIPS).
Lake Tahoe, Nevada, USA, 9 pages. .

(3) Learning Monadic and Dyadic Relations: Three Case Studies in Systems Biology
M. Stock, T. Pahikkala, A. Airola, T. Salakoski, B. De Baets and W. Waegeman
(2012) ECML WORKSHOP ON LEARNING AND DISCOVERY IN SYMBOLIC SYSTEMS BIOLOGY.
Bristol, UK, 12 pages. .

(2) An analysis of chaining in multi-label classification
K. Dembczynski, W. Waegeman and E. Hüllermeier
(2012) EUROPEAN CONFERENCE ON ARTIFICIAL INTELLIGENCE.
Montpellier, France, 294-299. Frontiers in Artificial Intelligence and Applications 242.

(1) F-Measure Maximization in Multilabel Classification
W. Cheng, K. Dembczynski, E. Hüllermeier, A. Jaroszewicz and W. Waegeman
(2012) JRC DATA MINING CONTEST.
, 8 pages. .

Date	Title
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

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

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