Benoît Frénay

ORCID

Publication Activity (10 Years)

Years Active: 2008-2024
Publications (10 Years): 64

Top Venues

Catholic University of Louvain, Louvain-la-Neuve, Belgium (PHD)

Education History

Catholic University of Louvain, Louvain-la-Neuve, Belgium

PHD

Publications

Rebecca Marion, Benoît Frénay
Improving the Feature Selection Stability of the Delta Test in Regression. IEEE Trans. Artif. Intell. 5 (5) (2024)
Pierre Poitier, Jérôme Fink, Benoît Frénay
Towards better transition modeling in recurrent neural networks: The case of sign language tokenization. Neurocomputing 567 (2024)
Mohammed El Adoui, Thomas Herpoel, Benoît Frénay
Constrained Tiny Machine Learning for Predicting Gas Concentration with I4.0 Low-cost Sensors. ACM Trans. Embed. Comput. Syst. 23 (3) (2024)
Arnaud Bougaham, Mohammed El Adoui, Isabelle Linden, Benoît Frénay
Composite score for anomaly detection in imbalanced real-world industrial dataset. Mach. Learn. 113 (7) (2024)
Géraldin Nanfack, Paul Temple, Benoît Frénay
Learning Customised Decision Trees for Domain-knowledge Constraints. Pattern Recognit. 142 (2023)
Armielle Noulapeu Ngaffo, Julien Albert, Benoît Frénay, Gilles Perrouin
FairBayRank: A Fair Personalized Bayesian Ranker. ESANN (2023)
Cristina Morariu, Adrien Bibal, René Cutura, Benoît Frénay, Michael Sedlmair
Predicting User Preferences of Dimensionality Reduction Embedding Quality. IEEE Trans. Vis. Comput. Graph. 29 (1) (2023)
Hendrik Blockeel, Laurens Devos, Benoît Frénay, Géraldin Nanfack, Siegfried Nijssen
Decision trees: from efficient prediction to responsible AI. Frontiers Artif. Intell. 6 (2023)
Sédrick Stassin, Alexandre Englebert, Géraldin Nanfack, Julien Albert, Nassim Versbraegen, Gilles Peiffer, Miriam Doh, Nicolas Riche, Benoît Frénay, Christophe De Vleeschouwer
An Experimental Investigation into the Evaluation of Explainability Methods. CoRR (2023)
Adrien Bibal, Valentin Delchevalerie, Benoît Frénay
DT-SNE: t-SNE discrete visualizations as decision tree structures. Neurocomputing 529 (2023)
Arnaud Bougaham, Valentin Delchevalerie, Mohammed El Adoui, Benoît Frénay
Industrial and Medical Anomaly Detection Through Cycle-Consistent Adversarial Networks. CoRR (2023)
Jérôme Fink, Mathieu De Coster, Joni Dambre, Benoît Frénay
Trends and Challenges for Sign Language Recognition with Machine Learning. ESANN (2023)
Valentin Delchevalerie, Alexandre Mayer, Adrien Bibal, Benoît Frénay
SO(2) and O(2) Equivariance in Image Recognition with Bessel-Convolutional Neural Networks. CoRR (2023)
Jérôme Fink, Pierre Poitier, Maxime André, Loup Meurice, Benoît Frénay, Anthony Cleve, Bruno Dumas, Laurence Meurant
Sign Language-to-Text Dictionary with Lightweight Transformer Models. IJCAI (2023)
Benoît Frénay
A Counterexample to Ockham's Razor and the Curse of Dimensionality: Marginalising Complexity and Dimensionality for GMMs. ESANN (2023)
Adrien Bibal, Tassadit Bouadi, Benoît Frénay, Luis Galárraga, José Oramas
AIMLAI: Advances in Interpretable Machine Learning and Artificial Intelligence. CIKM (2022)
Pierre Poitier, Jérôme Fink, Benoît Frénay
Towards Better Transition Modeling in Recurrent Neural Networks: the Case of Sign Language Tokenization. ESANN (2022)
Abiola Paterne Chokki, Anthony Simonofski, Antoine Clarinval, Benoît Frénay, Benoît Vanderose
Fostering Interaction Between Open Government Data Stakeholders: An Exchange Platform for Citizens, Developers and Publishers. EGOV (2022)
Thibaut Capuano, Houari A. Sahraoui, Benoît Frénay, Benoît Vanderose
Learning from Code Repositories to Recommend Model Classes. J. Object Technol. 21 (3) (2022)
Abiola Paterne Chokki, Rabeb Abida, Benoît Frénay, Benoît Vanderose, Anthony Cleve
ODSAG: Enhancing Open Data Discoverability and Understanding through Semantic Annotation (short paper). EGOV-CeDEM-ePart-* (2022)
Géraldin Nanfack, Paul Temple, Benoît Frénay
Constraint Enforcement on Decision Trees: A Survey. ACM Comput. Surv. 54 (10s) (2022)
Abiola Paterne Chokki, Anthony Simonofski, Benoît Frénay, Benoît Vanderose
Increasing Awareness and Usefulness of Open Government Data: An Empirical Analysis of Communication Methods. RCIS (2022)
Viet Minh Vu, Adrien Bibal, Benoît Frénay
Integrating Constraints Into Dimensionality Reduction for Visualization: A Survey. IEEE Trans. Artif. Intell. 3 (6) (2022)
Abiola Paterne Chokki, Anthony Simonofski, Benoît Frénay, Benoît Vanderose
Engaging Citizens with Open Government Data: The Value of Dashboards Compared to Individual Visualizations. Digit. Gov. Res. Pract. 3 (3) (2022)
Arnaud Bougaham, Mohammed El Adoui, Isabelle Linden, Benoît Frénay
Composite Score for Anomaly Detection in Imbalanced Real-World Industrial Dataset. CoRR (2022)
Abiola Paterne Chokki, Benoît Frénay, Benoît Vanderose
Open Data Explorer: An End-to-end Tool for Data Storytelling using Open Data. AMCIS (2022)
Jérôme Fink, Benoît Frénay, Laurence Meurant, Anthony Cleve
LSFB-CONT and LSFB-ISOL: Two New Datasets for Vision-Based Sign Language Recognition. IJCNN (2021)
Abiola Paterne Chokki, Anthony Simonofski, Benoît Frénay, Benoît Vanderose
Open Government Data for Non-expert Citizens: Understanding Content and Visualizations' Expectations. RCIS (2021)
Arnaud Bougaham, Adrien Bibal, Isabelle Linden, Benoît Frénay
GanoDIP - GAN Anomaly Detection through Intermediate Patches: a PCBA Manufacturing Case. LIDTA@ECML/PKDD (2021)
Benoît Vanderose, Julie Henry, Benoît Frénay, Xavier Devroey
Report from the 2nd Int. Workshop on Education through Advanced Software Engineering and Artificial Intelligence (EASEAI '20). ACM SIGSOFT Softw. Eng. Notes 46 (2) (2021)
Adrien Bibal, Michael Lognoul, Alexandre de Streel, Benoît Frénay
Legal requirements on explainability in machine learning. Artif. Intell. Law 29 (2) (2021)
Pieter Delobelle, Paul Temple, Gilles Perrouin, Benoît Frénay, Patrick Heymans, Bettina Berendt
Ethical Adversaries: Towards Mitigating Unfairness with Adversarial Machine Learning. SIGKDD Explor. 23 (1) (2021)
Adrien Bibal, Rebecca Marion, Rainer von Sachs, Benoît Frénay
BIOT: Explaining multidimensional nonlinear MDS embeddings using the Best Interpretable Orthogonal Transformation. Neurocomputing 453 (2021)
Adrien Bibal, Antoine Clarinval, Bruno Dumas, Benoît Frénay
IXVC: An interactive pipeline for explaining visual clusters in dimensionality reduction visualizations with decision trees. Array 11 (2021)
Valentin Delchevalerie, Alexandre Mayer, Adrien Bibal, Benoît Frénay
Accelerating $t$-SNE using Fast Fourier Transforms and the Particle-Mesh Algorithm from Physics. IJCNN (2021)
Alexandra Degeest, Benoît Frénay, Michel Verleysen
Reading grid for feature selection relevance criteria in regression. Pattern Recognit. Lett. 148 (2021)
Quentin Vaneck, Thomas Colart, Benoît Frénay, Benoît Vanderose
A tool for evaluating computer programs from students. EASEAI@ESEC/SIGSOFT FSE (2021)
Viet Minh Vu, Adrien Bibal, Benoît Frénay
iPMDS: Interactive Probabilistic Multidimensional Scaling. IJCNN (2021)
Géraldin Nanfack, Paul Temple, Benoît Frénay
Global explanations with decision rules: a co-learning approach. UAI (2021)
Viet Minh Vu, Adrien Bibal, Benoît Frénay
Constraint Preserving Score for Automatic Hyperparameter Tuning of Dimensionality Reduction Methods for Visualization. IEEE Trans. Artif. Intell. 2 (3) (2021)
Cristina Morariu, Adrien Bibal, René Cutura, Benoît Frénay, Michael Sedlmair
DumbleDR: Predicting User Preferences of Dimensionality Reduction Projection Quality. CoRR (2021)
Valentin Delchevalerie, Adrien Bibal, Benoît Frénay, Alexandre Mayer
Achieving Rotational Invariance with Bessel-Convolutional Neural Networks. NeurIPS (2021)
Géraldin Nanfack, Valentin Delchevalerie, Benoît Frénay
Boundary-Based Fairness Constraints in Decision Trees and Random Forests. ESANN (2021)
Viet Minh Vu, Adrien Bibal, Benoît Frénay
HCt-SNE: Hierarchical Constraints with t-SNE. IJCNN (2021)
Adrien Bibal, Viet Minh Vu, Géraldin Nanfack, Benoît Frénay
Explaining t-SNE Embeddings Locally by Adapting LIME. ESANN (2020)
Pieter Delobelle, Paul Temple, Gilles Perrouin, Benoît Frénay, Patrick Heymans, Bettina Berendt
Ethical Adversaries: Towards Mitigating Unfairness with Adversarial Machine Learning. CoRR (2020)
Adrien Bibal, Michael Lognoul, Alexandre de Streel, Benoît Frénay
Impact of Legal Requirements on Explainability in Machine Learning. CoRR (2020)
Benoît Vanderose, Benoît Frénay, Julie Henry, Xavier Devroey
Report from the 1st Int. Workshop on Education through Advanced Software Engineering and Artificial Intelligence (EASEAI '19). ACM SIGSOFT Softw. Eng. Notes 45 (1) (2020)
Adrien Bibal, Tassadit Bouadi, Benoît Frénay, Luis Galárraga, José Oramas
AIMLAI'20: Third Workshop on Advances in Interpretable Machine Learning and Artificial Intelligence. CIKM (2020)
Martin Weyssow, Houari A. Sahraoui, Benoît Vanderose, Benoît Frénay
Function completion in the time of massive data: A code embedding perspective. CoRR (2020)
Viet Minh Vu, Benoît Frénay
User-steering interpretable visualization with probabilistic principal components analysis. ESANN (2019)
Alexandra Degeest, Michel Verleysen, Benoît Frénay
About Filter Criteria for Feature Selection in Regression. IWANN (2) (2019)
Jérôme Fink, Anthony Cleve, Benoît Frénay
Deep Learning Applied to Sign Language. BNAIC/BENELEARN (2019)
Alexandra Degeest, Michel Verleysen, Benoît Frénay
Comparison Between Filter Criteria for Feature Selection in Regression. ICANN (2) (2019)
Rebecca Marion, Adrien Bibal, Benoît Frénay
BIR: A method for selecting the best interpretable multidimensional scaling rotation using external variables. Neurocomputing 342 (2019)
Benoît Frénay, Bruno Dumas, John A. Lee
Information visualisation and machine learning: latest trends towards convergence. ESANN (2018)
Alexandra Degeest, Michel Verleysen, Benoît Frénay
Smoothness Bias in Relevance Estimators for Feature Selection in Regression. AIAI (2018)
Adrien Bibal, Rebecca Marion, Benoît Frénay
Finding the most interpretable MDS rotation for sparse linear models based on external features. ESANN (2018)
Lauriane Castin, Benoît Frénay
clustering with decision trees: divisive and agglomerative approach. ESANN (2018)
Benoît Frénay, Barbara Hammer
Label-noise-tolerant classification for streaming data. IJCNN (2017)
Adrien Bibal, Benoît Frénay
Learning Interpretability for Visualizations using Adapted Cox Models through a User Experiment. CoRR (2016)
Benoît Frénay, Michel Verleysen
Reinforced Extreme Learning Machines for Fast Robust Regression in the Presence of Outliers. IEEE Trans. Cybern. 46 (12) (2016)
Benoît Frénay, Bruno Dumas
Information visualisation and machine learning: characteristics, convergence and perspective. ESANN (2016)
Adrien Bibal, Benoît Frénay
Interpretability of machine learning models and representations: an introduction. ESANN (2016)
Alexandra Degeest, Michel Verleysen, Benoît Frénay
Feature ranking in changing environments where new features are introduced. IJCNN (2015)
Samuel Branders, Benoît Frénay, Pierre Dupont
Survival Analysis with Cox Regression and Random Non-linear Projections. ESANN (2015)
Benoît Frénay, Ata Kabán
Special issue on advances in learning with label noise. Neurocomputing 160 (2015)
Benoît Frénay, Ata Kabán
A comprehensive introduction to label noise. ESANN (2014)
Alexandra Degeest, Benoît Frénay, Michel Verleysen
Automatic correction of SVM for drifted data classification. EGC (2014)
Benoît Frénay, Gauthier Doquire, Michel Verleysen
Estimating mutual information for feature selection in the presence of label noise. Comput. Stat. Data Anal. 71 (2014)
Benoît Frénay, Michel Verleysen
Classification in the Presence of Label Noise: A Survey. IEEE Trans. Neural Networks Learn. Syst. 25 (5) (2014)
Benoît Frénay, Daniela Hofmann, Alexander Schulz, Michael Biehl, Barbara Hammer
Valid interpretation of feature relevance for linear data mappings. CIDM (2014)
Benoît Frénay, Michel Verleysen
Pointwise probability reinforcements for robust statistical inference. Neural Networks 50 (2014)
Benoît Frénay, Gauthier Doquire, Michel Verleysen
Is mutual information adequate for feature selection in regression? Neural Networks 48 (2013)
Gauthier Doquire, Benoît Frénay, Michel Verleysen
Risk Estimation and Feature Selection. ESANN (2013)
Benoît Frénay, Mark van Heeswijk, Yoan Miche, Michel Verleysen, Amaury Lendasse
Feature selection for nonlinear models with extreme learning machines. Neurocomputing 102 (2013)
Benoît Frénay, Gauthier Doquire, Michel Verleysen
Theoretical and empirical study on the potential inadequacy of mutual information for feature selection in classification. Neurocomputing 112 (2013)
Benoît Frénay, Gauthier Doquire, Michel Verleysen
On the Potential Inadequacy of Mutual Information for Feature Selection. ESANN (2012)
Benoît Frénay, Michel Verleysen
Parameter-insensitive kernel in extreme learning for non-linear support vector regression. Neurocomputing 74 (16) (2011)
Benoît Frénay, Gaël de Lannoy, Michel Verleysen
Label Noise-Tolerant Hidden Markov Models for Segmentation: Application to ECGs. ECML/PKDD (1) (2011)
Benoît Frénay, Michel Verleysen
Using SVMs with randomised feature spaces: an extreme learning approach. ESANN (2010)
Benoît Frénay, Marco Saerens
, a simple reinforcement learning scheme for two-player zero-sum Markov games. Neurocomputing 72 (7-9) (2009)
Benoît Frénay, Gaël de Lannoy, Michel Verleysen
Improving the transition modelling in hidden Markov models for ECG segmentation. ESANN (2009)
Benoît Frénay, Marco Saerens
QL2, a simple reinforcement learning scheme for two-player zero-sum Markov games. ESANN (2008)

Benoît Frénay.css-eqlu8i{font-size:small;padding-left:4px;}

Publication Activity (10 Years)

Top Topics

Top Venues

Benoît Frénay