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Research Output 2007 2019

2019

BIR: A Method for Selecting the Best Interpretable Multidimensional Scaling Rotation using External Variables

Marion, R., Bibal, A. & Frenay, B., 4 Feb 2019, In : Neurocomputing. 342, p. 83-96 14 p.

Research output: Contribution to journalArticle

File
Ecology
Invariance
Psychology
69 Downloads (Pure)
Open Access
File
3 Downloads (Pure)

Measuring Quality and Interpretability of Dimensionality Reduction Visualizations

Bibal, A. & Frenay, B., 2019, SafeML ICLR Workshop. New Orleans, Louisiana

Research output: Contribution in Book/Catalog/Report/Conference proceedingConference contribution

Open Access
File
Visualization
Learning systems
3 Downloads (Pure)

User-Based Experiment Guidelines for Measuring Interpretability in Machine Learning

Bibal, A., Dumas, B. & Frenay, B., 2019, EGC Workshop on Advances in Interpretable Machine Learning and Artificial Intelligence. Metz

Research output: Contribution in Book/Catalog/Report/Conference proceedingConference contribution

Open Access
File
Learning systems
Human computer interaction
Experiments

User-steering Interpretable Visualization with Probabilistic Principal Components Analysis

Vu, V. M. & Frenay, B., 28 Mar 2019, ESANN 2019 - Proceedings: 27th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. i6doc.com publication, p. 349-354 6 p.

Research output: Contribution in Book/Catalog/Report/Conference proceedingConference contribution

Open Access
File
Principal component analysis
Visualization
Learning systems
Feedback
2018
13 Downloads (Pure)

AI in a Nutshell : Three Hands-on Activities for Teenagers

Dumas, B., Frenay, B., Henry, J., Smal, A., Collard, A-S. & Hernalesteen, A., Jun 2018, (Unpublished). 4 p.

Research output: Contribution to conferencePaper

File
artificial intelligence
emotion
expert
Teaching
resources
1 Downloads (Pure)

Comprendre l’ordinateur à travers un système informatique tangible, le micro:bit

Théate, N., Smal, A., Frenay, B. & Henry, J., 27 Mar 2018, Une école numérique pour émanciper ?: Colloque scientifique, Actes de la conférence. 4 p.

Research output: Contribution in Book/Catalog/Report/Conference proceedingConference contribution

Open Access
File
5 Downloads (Pure)

Finding the Most Interpretable MDS Rotation for Sparse Linear Models based on External Features

Bibal, A., Marion, R. & Frenay, B., 2018, 26th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. Bruges, p. 537-542 7 p.

Research output: Contribution in Book/Catalog/Report/Conference proceedingConference contribution

Open Access
File
5 Downloads (Pure)

Intelligence Artificielle: Éduquer pour modifier la représentation qu’en ont les jeunes

Olivier, B., Smal, A., Frenay, B. & Henry, J., 27 Mar 2018, Une école numérique pour émanciper ?: Colloque scientifique, Actes de la conférence. p. 34-37 4 p.

Research output: Contribution in Book/Catalog/Report/Conference proceedingConference contribution

Open Access
File

Interaction and User Integration in Machine Learning for Information Visualisation

Dumas, B., Frenay, B. & Lee, J., 25 Apr 2018, ESANN 2018 proceedings, European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. i6doc.com.publ., p. 97-104 8 p. (ESANN 2018 - Proceedings, European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning).

Research output: Contribution in Book/Catalog/Report/Conference proceedingConference contribution

Learning systems
Visualization
Navigation
Feedback
2017

Enseigner la programmation à l'université : challenges didactiques et pédagogiques

Frenay, B., 2017, L'informatique et le numérique dans la classe : qui, comment, pourquoi ?. Presses universitaires de Namur

Research output: Contribution in Book/Catalog/Report/Conference proceedingChapter

Label-noise-tolerant classification for streaming data

Frenay, B. & Hammer, B., 30 Jun 2017, 2017 International Joint Conference on Neural Networks, IJCNN 2017 - Proceedings. Institute of Electrical and Electronics Engineers Inc., Vol. 2017-May. p. 1748-1755 8 p. 7966062

Research output: Contribution in Book/Catalog/Report/Conference proceedingConference contribution

Open Access
File
Labels
Vector quantization
Labeling
Learning systems
Big data
2016

Enseigner la programmation à travers un EDI enrichi

Henry, J. & Frenay, B., Jan 2016, (Unpublished).

Research output: Contribution to conferencePoster

Information Visualisation and Machine Learning: Characteristics, Convergence and Perspective

Frenay, B. & Dumas, B., 29 Apr 2016, ESANN 2016: Proceedings of the European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. i6doc.com publication, p. 623-628 6 p.

Research output: Contribution in Book/Catalog/Report/Conference proceedingConference contribution

Learning systems
Visualization
Data reduction
615 Downloads (Pure)

Interpretability of Machine Learning Models and Representations: an Introduction

Bibal, A. & Frenay, B., 2016, 24th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. Bruges, p. 77-82

Research output: Contribution in Book/Catalog/Report/Conference proceedingConference contribution

Open Access
File
heuristics
learning
27 Downloads (Pure)

Introduction to Interpretability in Machine Learning

Bibal, A. & Frenay, B., 2016, BENELEARN 2016. Kortrijk

Research output: Contribution in Book/Catalog/Report/Conference proceedingConference contribution

Open Access
File
21 Downloads (Pure)

Learning Interpretability for Visualizations using Adapted Cox Models through a User Experiment

Bibal, A. & Frenay, B., 2016, NIPS Workshop on Interpretable Machine Learning in Complex Systems. Barcelona

Research output: Contribution in Book/Catalog/Report/Conference proceedingConference contribution

Open Access
File
Conservation
Visualization
Experiments

Robustifying Maximum Likelihood Inference

Frenay, B. & Verleysen, M., 2016, BENELEARN 2016. Kortrijk

Research output: Contribution in Book/Catalog/Report/Conference proceedingConference contribution

2015

Feature ranking in changing environments where new features are introduced

Degeest, A., Verleysen, M. & Frénay, B., 28 Sep 2015, Proceedings of the International Joint Conference on Neural Networks. Institute of Electrical and Electronics Engineers Inc., Vol. 2015-September. p. 1-8 8 p. 7280533

Research output: Contribution in Book/Catalog/Report/Conference proceedingConference contribution

Feature extraction
Learning systems
Sensors

Reinforced extreme learning machines for fast robust regression in the presence of outliers

Frenay, B. & Verleysen, M., 17 Dec 2015, In : IEEE Transactions on Cybernetics. PP, 99, p. 3351-3363 7358117.

Research output: Contribution to journalArticle

Learning systems
Neurons
Reinforcement
Experiments

Survival analysis with Cox regression and random non-linear projections

Branders, S., Frénay, B. & Dupont, P., 2015, 23rd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2015 - Proceedings. i6doc.com publication, p. 119-124 6 p.

Research output: Contribution in Book/Catalog/Report/Conference proceedingConference contribution

Hazards

Valid interpretation of feature relevance for linear data mappings

Frenay, B., Hofmann, D., Schulz, A., Biehl, M. & Hammer, B., 13 Jan 2015, IEEE SSCI 2014 - 2014 IEEE Symposium Series on Computational Intelligence - CIDM 2014: 2014 IEEE Symposium on Computational Intelligence and Data Mining, Proceedings. Institute of Electrical and Electronics Engineers Inc., p. 149-156 8 p. 7008661

Research output: Contribution in Book/Catalog/Report/Conference proceedingChapter (peer-reviewed)

Linear transformations
Linear regression
Linear programming
Learning algorithms
Learning systems
2014

A Comprehensive Introduction to Label Noise: Proceedings of the 2014 European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2014)

Frénay, B. & Kaban, A., 2014, Proceedings of the 2014 European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2014). i6doc.com.publ.

Research output: Contribution in Book/Catalog/Report/Conference proceedingChapter (peer-reviewed)

Artificial intelligence
Learning systems
Labels
Neural networks

Automatic Correction of SVM for Drifted Data Classification: Proceedings de la 14 ème conférence Extraction et Gestion des Connaissances (EGC 2014)

Degeest, A., Frénay, B. & Verleysen, M., 2014, Proceedings de la 14 ème conférence Extraction et Gestion des Connaissances (EGC 2014).

Research output: Contribution in Book/Catalog/Report/Conference proceedingChapter (peer-reviewed)

Support vector machines
Learning systems

Classification in the presence of label noise: A survey

Frénay, B. & Verleysen, M., 2014, In : IEEE Transactions on Neural Networks and Learning Systems. 25, 5, p. 845-869 25 p., 6685834.

Research output: Contribution to journalArticle

Open Access
File
Labels
Taxonomies
Design of experiments

Estimating Mutual information for feature selection in the presence of label noise

Frénay, B., Doquire, G. & Verleysen, M., Mar 2014, In : Computational Statistics and Data Analysis. 71, p. 832-848 17 p.

Research output: Contribution to journalArticle

Mutual Information
Feature Selection
Feature extraction
Labels
Classification Problems

Pointwise probability reinforcements for robust statistical inference

Frénay, B. & Verleysen, M., 2014, In : Neural Networks. 50, p. 124-141 18 p.

Research output: Contribution to journalArticle

File
Reinforcement
Observation
Learning systems
Experiments
2013

Feature selection for nonlinear models with extreme learning machines

Frénay, B., van Heeswijk, M., Miche, Y., Verleysen, M. & Lendasse, A., 2013, In : Neurocomputing. 102, p. 111-124 14 p.

Research output: Contribution to journalArticle

Nonlinear Dynamics
Learning systems
Feature extraction
Statistics
Machine Learning

Is mutual information adequate for feature selection in regression?

Frénay, B., Doquire, G. & Verleysen, M., Dec 2013, In : Neural Networks. 48, p. 1-7 7 p.

Research output: Contribution to journalArticle

Feature extraction
Learning systems
Machine Learning

Mutual Information: an Adequate Tool for Feature Selection: Proceedings of the 22nd edition of the annual Belgian-Dutch Conference on Machine Learning (BENELEARN 2013)

Frénay, B., Doquire, G. & Verleysen, M., 2013, Proceedings of the 22nd edition of the annual Belgian-Dutch Conference on Machine Learning (BENELEARN 2013).

Research output: Contribution in Book/Catalog/Report/Conference proceedingChapter (peer-reviewed)

Risk Estimation and Feature Selection: Proceedings of European Symposium on Artificial Neural Networks (ESANN 2013)

Doquire, G., Frénay, B. & Verleysen, M., 2013, ESANN 2013 proceedings, 21st European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. p. 161-166 6 p.

Research output: Contribution in Book/Catalog/Report/Conference proceedingChapter (peer-reviewed)

Feature extraction
Neural networks
Experiments

Theoretical and empirical study on the potential inadequacy of mutual information for feature selection in classification

Frénay, B., Doquire, G. & Verleysen, M., 18 Jul 2013, In : Neurocomputing. 112, p. 64-78 15 p.

Research output: Contribution to journalArticle

File
Patient Selection
Feature extraction
Theoretical Models
Heuristics
Experiments

Uncertainty and label noise in machine learning

Verleysen, M. & Frénay, B., 2013, Université catholique de Louvain (UCL).

Research output: External Thesis Doctoral Thesis

Learning systems
Labels
Feature extraction
Feedforward neural networks
Electrocardiography
2012

On the Potential Inadequacy of Mutual Information for Feature Selection: Proceedings of the 20th International Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2012)

Frénay, B., Doquire, G. & Verleysen, M., 2012, Proceedings of the 20th International Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2012). i6doc.com

Research output: Contribution in Book/Catalog/Report/Conference proceedingChapter (peer-reviewed)

Artificial intelligence
Learning systems
Feature extraction
Neural networks
2011

Ensembles of local linear models for bankruptcy analysis and prediction

Kainulainen, L., Miche, Y., Eirola, E., Yu, Q., Frenay, B., Séverin, E. & Lendasse, A., 2011, In : Case Studies in Business, Industry and Government Statistics. 4, 2, p. 116–133

Research output: Contribution to journalArticle

Label Noise-Tolerant Hidden Markov Models for Segmentation: Application to ECGs

Frénay, B., de Lannoy, G. & Verleysen, M., 2011, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). PART 1 ed. Vol. 6911 LNAI. p. 455-470 16 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 6911 LNAI, no. PART 1).

Research output: Contribution in Book/Catalog/Report/Conference proceedingChapter (peer-reviewed)

Hidden Markov models
Electrocardiography
Markov Model
Labels
Segmentation

Parameter-insensitive kernel in extreme learning for non-linear support vector regression

Frénay, B. & Verleysen, M., Sep 2011, In : Neurocomputing. 74, 16, p. 2526-2531 6 p.

Research output: Contribution to journalArticle

Learning
Computational complexity
Experiments
2010

Clustering patterns of urban built-up areas with curves of fractal scaling behaviour

Thomas, I., Frankhauser, P., Frenay, B., Verleysen, M. & Samos-Matisse, S. M., 2010, In : Environment and Planning B: Planning & Design. 37, 5, p. 942-954 13 p.

Research output: Contribution to journalArticle

Fractal dimension
scaling
Fractals
Textures
Planning

Using SVMs with randomised feature spaces: an extreme learning approach: Proceedings of the 18th European Symposium on Artificial Neural Networks - Computational Intelligence and Machine Learning (ESANN 2010)

Frénay, B. & Verleysen, M., 2010, Proceedings of the 18th European Symposium on Artificial Neural Networks - Computational Intelligence and Machine Learning, ESANN 2010. p. 315-320 6 p.

Research output: Contribution in Book/Catalog/Report/Conference proceedingChapter (peer-reviewed)

Artificial intelligence
Learning systems
Neural networks
Neurons
Classifiers
2009

Clustering fractal urban patterns with curves of scaling behavior: Proceedings of the 49th Congress of the European Regional Science Association "Territorial cohesion of Europe and integrative planning" (ERSA 2009)

Thomas, I., Frankhauser, P., Frénay, B. & Verleysen, M., 2009, Proceedings of the 49th Congress of the European Regional Science Association "Territorial cohesion of Europe and integrative planning" (ERSA 2009).

Research output: Contribution in Book/Catalog/Report/Conference proceedingChapter (peer-reviewed)

Clustering patterns of urban builtup areas with curves of fractal scaling behavior

THOMAS, I., Frankhauser, P., Frenay, B. & Verleysen, M., 2009, Proc. ASRDLF.

Research output: Contribution in Book/Catalog/Report/Conference proceedingChapter (peer-reviewed)

Improving the transition modelling in hidden Markov models for ECG segmentation: Proceedings of the 17th European Symposium on Artificial Neural Networks - Advances in Computational Intelligence and Learning (ESANN 2009)

Frénay, B., de Lannoy, G. & Verleysen, M., 2009, ESANN 2009 Proceedings, 17th European Symposium on Artificial Neural Networks - Advances in Computational Intelligence and Learning. p. 141-146 6 p.

Research output: Contribution in Book/Catalog/Report/Conference proceedingChapter (peer-reviewed)

Hidden Markov models
Electrocardiography
Artificial intelligence
Neural networks
Bayesian networks

QL2, a simple reinforcement learning scheme for two-player zero-sum Markov games: Proceedings of the 16th European Symposium on Artificial Neural Networks

Frénay, B. & Saerens, M., 2009, Proceedings of the 16th European Symposium on Artificial Neural Networks. p. 137-142 6 p.

Research output: Contribution in Book/Catalog/Report/Conference proceedingChapter (peer-reviewed)

Reinforcement learning
Ashes
Neural networks
Learning algorithms
Learning systems
2008

Emission Modelling for Supervised ECG Segmentation using Finite Differences: Proceedings of the 4th European Conference of the International Federation for Medical and Biological Engineering - MBEC 2008

Frénay, B., de Lannoy, G. & Verleysen, M., 2008, Proceedings of the 4th European Conference of the International Federation for Medical and Biological Engineering - MBEC 2008. Vander Sloten, J., Nyssen, M., Verdonck, P. & Haueisen, J. (eds.). Springer Verlag, Vol. 22. p. 1212-1216 5 p.

Research output: Contribution in Book/Catalog/Report/Conference proceedingChapter (peer-reviewed)

Electrocardiography
Hidden Markov models
Wavelet transforms
Derivatives
Bioengineering

QL2, a simple reinforcement learning scheme for two-player zero-sum Markov games

Frénay, B. & Saerens, M., 2008, In : Neurocomputing. 72, 7-9, p. 1494-1507 14 p.

Research output: Contribution to journalArticle

Reinforcement learning
Learning
Ashes
Boidae
Learning algorithms

Supervised ECG Delineation Using the Wavelet Transform and Hidden Markov Models: Proceedings of the 4th European Conference of the International Federation for Medical and Biological Engineering (MBEC 2008)

de Lannoy, G., Frénay, B., Verleysen, M. & Delbeke, J., 2008, Proceedings of the 4th European Conference of the International Federation for Medical and Biological Engineering (MBEC 2008). Vander Sloten, J., Nyssen, M., Verdonck, P. & Haueisen, J. (eds.). Springer Verlag, Vol. 22. p. 22-25 4 p.

Research output: Contribution in Book/Catalog/Report/Conference proceedingChapter (peer-reviewed)

Hidden Markov models
Electrocardiography
Wavelet transforms
Heuristic methods
Drug products