CEUR-WS.org/Vol-2491 - Proceedings of the Reference AI & ML Conference for Belgium, Netherlands & Luxemburg 2019

CEUR-WS.org/Vol-2491 - Proceedings of the Reference AI & ML Conference for Belgium, Netherlands & Luxemburg 2019
Vol-2491
urn:nbn:de:0074-2491-5
Copyright © 2019 for the individual papers by the papers' authors.
Copyright ©
2019
for the volume
as a collection by its editors.
This volume and its papers are published under the
Creative Commons License Attribution 4.0 International
(CC BY 4.0)
BNAIC/BENELEARN 2019
Proceedings of the Reference AI & ML Conference for Belgium, Netherlands & Luxemburg
Proceedings of the 31st Benelux Conference on Artificial Intelligence (BNAIC 2019) and the 28th Belgian Dutch Conference on Machine Learning (Benelearn 2019)
Brussels, Belgium, November 6-8, 2019
Edited by
Katrien Beuls
Bart Bogaerts
Gianluca Bontempi
**
Pierre Geurts
***
Nick Harley
Bertrand Lebichot
**
Tom Lenaerts
**
Gilles Louppe
***
Paul Van Eecke
Vrije Universiteit Brussel
, Belgium
**
Université Libre de Bruxelles
, Belgium
***
Université de Liège
, Belgium
Table of Contents
Preface
ML1: Applied Machine Learning
Understanding Telecom Customer Churn with Machine Learning: From Prediction to Causal Inference
(abstract; invited to postproceedings)
Théo Verhelst
Olivier Caelen
Jean-Christophe Dewitte
Bertrand Lebichot
Gianluca Bontempi
Paired Supervised Learning and Unsupervised Pretraining of CNN-Architecture for Violence Detection in Videos
(abstract; invited to postproceedings)
Abel Díaz Berenguer
Meshia Cédric Oveneke
Mitchel Alioscha-Perez
Hichem Sahli
Data-Driven Policy on Feasibility Determination for the Train Shunting Problem
(extended abstract)
Paulo Roberto de Oliveira da Costa
Jason Rhuggenaath
Yingqian Zhang
Alp Akcay
Wan-Jui Lee
Uzay Kaymak
News Topic Recommendation Using an Extended Bayesian Personalized Ranking
(abstract; invited to postproceedings)
Alireza Gharahighehi
Celine Vens
Analysing Visitor Flow Using a Bluetooth Positioning System
(thesis abstract)
Pieter van den Ham
Bert Bredeweg
Maartje Raijmakers
ML2: Deep Learning
Cross-Domain Neural-Kernel Networks
(extended abstract)
Siamak Mehrkanoon
Interpreting and Explaining Deep Models Visually
(extended abstract)
Jose Oramas
Kaili Wang
Tinne Tuytelaars
DeepProbLog: Neural Probabilistic Logic Programming
(extended abstract)
Robin Manhaeve
Sebastijan Dumancic
Angelika Kimmig
Thomas Demeester
Luc De Raedt
Temporal Factorization of 3D Convolutional Kernels
(short paper)
Gabrielle Ras
Luca Ambrogioni
Umut Guclu
Marcel van Gerven
Unsupervised Deep Feature Extraction for Neonatal Sleep Stage Classification
(thesis abstract)
Nick Seeuws
Amir Hossein Ansari
Sabine Van Huffel
Gunnar Naulaers
AI1: Constraint Programming
Stochastic Constraint Propagation for Mining Probabilistic Networks
(extended abstract)
Anna Louise Latour
Behrouz Babaki
Siegfried Nijssen
Generic Constraint-Based Block Modeling Using Constraint Programming
(extended abstract)
Alex Mattenet
Ian Davidson
Siegfried Nijssen
Pierre Schaus
Learning Optimal Decision Trees Using Constraint Programming
(extended abstract)
Hélène Verhaeghe
Siegfried Nijssen
Gilles Pesant
Claude-Guy Quimper
Pierre Schaus
Vehicle Routing by Learning from Historical Solutions
(extended abstract)
Rocsildes Canoy
Tias Guns
RP1: Applied Machine Learning
A Machine Learning-Based Approach for Predicting Tool Wear in Industrial Milling Processes
(extended abstract)
Mathias Van Herreweghe
Mathias Verbeke
Wannes Meert
Tom Jacobs
Predictive Maintenance of a Rotating Condenser Inside a Synchrocyclotron
(long paper)
Valentin Hamaide
François Glineur
Segmentation of Photovoltaic Panels in Aerial Photography Using Group Equivariant FCNs
(long paper)
Lars Bokkers
Luca Ambrogioni
Umut Güçlü
Partial Convolution Based Multimodal Autoencoder for Art Investigation
(long paper)
Xianghui Xie
Laurens Meeus
Aleksandra Pizurica
Time to Take Emoji Seriously: They Vastly Improve Casual Conversational Models
(short paper)
Pieter Delobelle
Bettina Berendt
Designing MacPherson Suspension Architectures Using Bayesian Optimization
(long paper)
Sinnu Susan Thomas
Jacopo Palandri
Mohsen Lakehal-Ayat
Punarjay Chakravarty
Friedrich Wolf-Monheim
Matthew Blaschko
Improving Machine Learning-Based Decision-Making Through Inclusion of Data Quality
(short paper)
Jens de Hoog
Siegfried Mercelis
Peter Hellinckx
Industrial Assets Performance Labelling Based on Numerically Encoded Event Logs
(long paper)
Pierre Dagnely
Tom Tourwé
Elena Tsiporkova
RP2: Applications of Artificial Intelligence
Deep Shared Representation Learning for Weather Elements Forecasting
(extended abstract)
Siamak Mehrkanoon
Failure Avoidance for Wind Turbines through Fleetwide Control
(extended abstract)
Timothy Verstraeten
Ann Nowé
Jan Helsen
Great Expectations & Aborted Business Initiatives: The Paradox of Social Robot Between Research and Industry
(short paper)
Silvia Tulli
Agustin Ambrossio
Amro Najjar
Francisco Javier Rodriguez Lera
End-To-End Anomaly Detection, Correction and Prediction of Missing Values in Historical Daily Temperature Timeseries
(abstract; invited to postproceedings)
Mitchel Alioscha-Perez
Meshia Cédric Oveneke
Abel Díaz Berenguer
Cédric Bertrand
Hichem Sahli
Learning to Transform, Combine, and Reason in Open-Domain Question Answering
(extended abstract)
Mostafa Dehghani
Hosein Azarbonyad
Jaap Kamps
Maarten de Rijke
The XAI paradox: Systems that Perform Well for the Wrong Reasons
(abstract; invited to postproceedings)
Cor Steging
Lambert Schomaker
Bart Verheij
Handling Unforeseen Failures Using Argumentation-Based Learning
(extended abstract)
Hamed Ayoobi
Ming Cao
Rineke Verbrugge
Bart Verheij
Autoencoder-Learned Local Image Descriptor for Image Inpainting
(long paper)
Nina Zizakic
Izumi Ito
Laurens Meeus
Aleksandra Pizurica
On Domination and Control in Strategic Ability
(extended abstract)
Damian Kurpiewski
Michał Knapik
Wojciech Jamroga
ML3: Applied ML & Machine Learning for Medicine
Cost-Efficient Segmentation of Electron Microscopy Images Using Active Learning
(abstract; invited to postproceedings)
Joris Roels
Yvan Saeys
Disentangled Variational Auto-Encoders for
Explaining ECG Beat Embeddings
(extended abstract)
Tom Van Steenkiste
Dirk Deschrijver
Tom Dhaene
Classification of Human White Blood Cells Using Machine Learning for Stain-Free Imaging Flow Cytometry
(extended abstract)
Maxim Lippeveld
Carly Knill
Emma Ladlow
Andrew Fuller
Louise J Michaelis
Yvan Saeys
Andrew Filby
Daniel Peralta
SMURFF: A High-Performance Framework for Matrix Factorization Methods
(extended abstract)
Tom Vander Aa
Imen Chakroun
Tom Ashby
Jaak Simm
Adam Arany
Yves Moreau
Thanh Le Van
José Felipe Golib Dzib
Jörg Wegner
Vladimir Chupakhin
Hugo Ceulemans
Roel Wuyts
Wilfried Verachtert
Predicting 120-Day Hospital Readmission Using Medical Administrative Patient Data
(thesis abstract)
Marijn van Wingerden
Jelle de Boer
Eric Postma
AI2: AI For Health & Medicine
Towards a Phylogenetic Measure to Quantify HIV Incidence
(abstract; invited to postproceedings)
Pieter Libin
Nassim Versbraegen
Ana Abecasis
Perpetua Gomes
Tom Lenaerts
Ann Nowé
A Residual Neural-Network Model to Predict Visual Cortex Measurements
(short paper)
Anne-Ruth José Meijer
Arnoud Visser
Data Mining for ADHD & ASD Prediction Based on Resting-State fMRI Signals: A Literature Review
(long paper)
Sarah Itani
Fabian Lecron
Philippe Fortemps
Integrating Clinically-Relevant Features into Skin Lesion Classification
(thesis abstract)
Emmeke Veltmeijer
Sezer Karaoglu
Theo Gevers
ML4: Supervised & Semi-Supervised Learning
An Aggregate Learning Approach for Interpretable Semi-Supervised Population Prediction and Disaggregation Using Ancillary Data
(extended abstract)
Guillaume Derval
Frédéric Docquier
Pierre Schaus
Set-Valued Prediction in Multi-Class Classification
(extended abstract)
Thomas Mortier
Marek Wydmuch
Krzysztof Dembczyński
Eyke Hüllermeier
Willem Waegeman
Calibrated Multi-Probabilistic Prediction as a Defense against Adversarial Attacks
(abstract; invited to postproceedings)
Jonathan Peck
Bart Goossens
Yvan Saeys
Machine Learning Methods for Ordinal Classification with Additional Relative Information
(abstract; invited to postproceedings)
Mengzi Tang
Raúl Pérez-Fernández
Bernard De Baets
AI3: Generative & Creative AI
Synthesizing Personality-Dependent Body Postures Using Generative Adversarial Networks
(long paper)
Frederik Calsius
Stylianos Asteriadis
Latent Space Exploration Using Generative Kernel PCA
(abstract; invited to postproceedings)
David Winant
Joachim Schreurs
Johan Suykens
Modelling Mutually Interactive Fictional Character Conversational Agents
(long paper)
Thomas Winters
Learning Hierarchical Spectral Representations of Human Speech with the Information Dynamics of Thinking
(thesis abstract)
Steven Homer
Crafting Conversational Agents’ Personality in a User-Centric Context
(thesis abstract)
Catia Ferreira
Sviatlana Hoehn
A Generative Policy Gradient Approach for Learning to Play Text-Based Adventure Games
(thesis abstract)
René Raab
Kurt Driessens
AI4: Natural Language
Training a Speech-to-Text Model for Dutch on the Corpus Gesproken Nederlands
(long paper)
Willem Röpke
Roxana Rădulescu
Kyriakos Efthymiadis
Ann Nowé
Question Similarity in Community Question Answering: A Systematic Exploration of Preprocessing Methods and Models
(extended abstract)
Florian Kunneman
Thiago Castro Ferreira
Antal van Den Bosch
Emiel Krahmer
Explaining Lexical Processing Times with Cognitively Plausible Computational Models
(abstract; invited to postproceedings)
Wietse de Vries
Target-Based Sentiment Analysis as a Sequence-Tagging Task
(long paper)
Zoe Gerolemou
Johannes C. Scholtes
RP3: Reinforcement Learning
Sample-Efficient Model-Free Reinforcement Learning with Off-Policy Critics
(extended abstract)
Denis Steckelmacher
Hélène Plisnier
Diederik M. Roijers
Ann Nowé
Action Learning and Grounding in Simulated Human-Robot Interactions
(extended abstract)
Oliver Roesler
Ann Nowé
A Reinforcement Learning Method to Select Ad Networks in Waterfall Strategy
(extended abstract)
Reza Refaei Afshar
Yingqian Zhang
Murat Firat
Uzay Kaymak
Transfer Reinforcement Learning across Environment Dynamics with Multiple Advisors
(long paper)
Hélène Plisnier
Denis Steckelmacher
Diederik M. Roijers
Ann Nowé
Maximum Entropy Bayesian Actor Critic
(long paper)
Steven Homer
Thompson Sampling for m-top Exploration
(extended abstract)
Pieter Libin
Timothy Verstraeten
Diederik Roijers
Wenjia Wang
Kristof Theys
Ann Nowé
Distillation of Deep Reinforcement Learning Models Using Fuzzy Inference Systems
(thesis abstract)
Arne Gevaert
Jonathan Peck
Yvan Saeys
RP4: Machine Learning for Bioinformatics & Life Science
Computer Aided Detection and Diagnosis System for Breast Cancer Detection Based on High Resolution 3D micro-CT Breast Microcalcifications
(extended abstract)
Redona Brahimetaj
Evgenia Papavasileiou
Frederik Temmermans
Bruno Cornelis
Inneke Willekens
Johan De Mey
Bart Jansen
Investigating Time Series Classification Techniques for Rapid Pathogen Identification with Single-Cell MALDI-TOF Mass Spectrum Data
(extended abstract)
Christina Papagiannopoulou
René Parchen
Willem Waegeman
ExCAPE-DB: An Integrated Large Scale Dataset Facilitating Big Data Analysis in Chemogenomics
(extended abstract)
Jiangming Sun
Nina Jeliazkova
Vladimir Chupakhin
Jose-Felipe Golib-Dzib
Lars Carlsson
Jörg Wegner
Hugo Ceulemans
Ivan Georgiev
Vedrin Jeliazkov
Nikolay Kochev
Thomas Ashby
Hongming Chen
Nonlinear Causality Inference in Microarray Time Series
(thesis abstract)
Fateme Nateghi Haredasht
Mohammad Hassan Moradi
A Study of Early Sepsis Detection Models Based on Multivariate Medical Time Series
(thesis abstract)
Aren Maes
Tom Van Steenkiste
Tom Dhaene
Dirk Deschrijver
ML5: Deep Learning & Reinforcement Learning
Deep Quality-Value (DQV) Learning
(extended abstract)
Matthia Sabatelli
Gilles Louppe
Pierre Geurts
Marco A. Wiering
Bayesian RL in Factored POMDPs
(extended abstract)
Sammie Katt
Frans Oliehoek
Chris Amato
HTMRL: Biologically Plausible Reinforcement Learning with Hierarchical Temporal Memory
(abstract; invited to postproceedings)
Jakob Struye
Kevin Mets
Steven Latré
Unconstrained Monotonic Neural Networks
(extended abstract)
Antoine Wehenkel
Gilles Louppe
ML6: Data & Network Mining
Conditional Network Embeddings
(extended abstract)
Bo Kang
Jefrey Lijffijt
Tijl De Bie
Adversarial Perturbations for Joint Entity and Relation Extraction
(extended abstract)
Giannis Bekoulis
Johannes Deleu
Thomas Demeester
Chris Develder
Towards Deterministic Diverse Subset Sampling
(abstract; invited to postproceedings)
Joachim Schreurs
Michael Fanuel
Johan Suykens
SubSect — An Interactive Itemset Visualization
(abstract; invited to postproceedings)
Joey De Pauw
Sandy Moens
Bart Goethals
AI5: Knowledge Representation & Hybrid AI
A Boxology of Design Patterns for Hybrid Learning and Reasoning Systems
(extended abstract)
Frank Van Harmelen
Annette ten Teije
Learning Optimal Classification Trees Using a Binary Linear Program Formulation
(extended abstract)
Sicco Verwer
Yingqian Zhang
SOGrounder: Modelling and Solving Second-Order Logic
(extended abstract)
Matthias van der Hallen
Gerda Janssens
An Interactive Knowledge Base Application for Group Assignment
(thesis abstract)
Simon Vandevelde
Kylian Van Dessel
Herman Crauwels
PARCo: A Knowledge-Based Agent for Context-Sensitive Reasoning and Decision-Making Regarding Privacy
(thesis abstract)
Andrei Popescu
Pinar Yolum
RP5: Supervised & Semi-Supervised Learning, Classification
Term Based Semantic Clusters for Very Short Text Classification
(extended abstract)
Jasper Paalman
Shantanu Mullick
Kalliopi Zervanou
Yingqian Zhang
Revision Classification for Current Events in Dutch Wikipedia Using a Long Short-Term Memory Network
(short paper)
Nienke Eijsvogel
Marijn Schraagen
Reduction Methods for Multi-Label Datasets Based on Granular Computing
(extended abstract)
Marilyn Bello
Gonzalo Nápoles
Koen Vanhoof
Rafael Bello
Scientific Machine Learning: Towards Predictive Closed-Form Models
(long paper)
Dimitri Papadimitriou
Steven Latre
Towards Automated Grading of UML Class Diagrams with Machine Learning
(long paper)
Dave Stikkolorum
Peter van der Putten
Caroline Sperandio
Michel Chaudron
Hierarchical Classification of Transposable Elements
(thesis abstract)
Felipe Kenji Nakano
Ricardo Cerri
RP6: Agents & Multi-Agent Systems
Privacy Norms in Online Social Networks
(extended abstract)
Onuralp Ulusoy
Pinar Yolum
What are we Measuring Anyway? A Literature Survey of Questionnaires Used in Studies Reported in the Intelligent Virtual Agent Conferences
(extended abstract)
Merijn Bruijnes
Siska Fitrianie
Deborah Richards
Amal Abdulrahman
Willem-Paul Brinkman
Improving Zero-Intelligence Plus for Call Markets
(short paper)
Jannick Hemelhof
Mihail Mihaylov
Ann Nowé
BS1: Best Student Papers
Iterative Model-Based Transfer in Deep Reinforcement Learning
(thesis abstract)
Jelmer Neeven
Continuous Exploitative Measurement Trajectories Using Bayesian Optimisation
(thesis abstract)
Rémi Delanghe
Tom Van Steenkiste
Dirk Deschrijver
Tom Dhaene
A Context Aware Deep Learning Architecture for Object Detection
(thesis abstract)
Kevin Bardool
Tinne Tuytelaars
Jose Oramas
Privacy Preserving Reinforcement Learning over Distributed Datasets
(thesis abstract)
Regis Loeb
Timothy Verstraeten
Ann Nowe
Ann Dooms
Formalization and Improvement of Ambulance Dispatching in Brabant-Zuidoost
(thesis abstract)
Nikki Theeuwes
Geert-Jan van Houtum
Yingqian Zhang
Björn Gadet
Automated Artemia Detection and Length Measurement Using Deep Convolutional Networks
(thesis abstract)
Gang Wang
Bernard De Baets
AI6: Multi-Agent Systems
Simulated Annealing as an Optimization Algorithm in the Automatic Modular Design of Robot Swarms
(abstract; invited to postproceedings)
Jonas Kuckling
Keneth Ubeda Arriaza
Mauro Birattari
Runtime Revision of Norms and Sanctions Based on Agent Preferences
(extended abstract)
Davide Dell'Anna
Mehdi Dastani
Fabiano Dalpiaz
Comparison of Different Exploration Schemes in the Automatic Modular Design of Robot Swarms
(abstract; invited to postproceedings)
Gaëtan Spaey
Miquel Kegeleirs
David Garzón Ramos
Mauro Birattari
AI7: Explainability
Investigating People’s Attitudes Towards AI with a Smart Photo Booth
(extended abstract)
Hanna Schraffenberger
Yana van de Sande
Gabi Schaap
Tibor Bosse
Explainable Robotics Applied to Bipedal Walking Gait Development
(long paper)
Nico Roos
Zhenglong Sun
Visualising the Training Process of Convolutional Neural Networks for Non-Experts
(long paper)
Michelle Peters
Lindsay Kempen
Meike Nauta
Christin Seifert
RP7: Deep Learning
Adversarial Variational Optimization of Non-Differentiable Simulators
(extended abstract)
Gilles Louppe
Joeri Hermans
Kyle Cranmer
A Systematic Analysis of a Context Aware Deep Learning Architecture for Object Detection
(long paper)
Kevin Bardool
Tinne Tuytelaars
Jose Oramas
A Scalable Logo Recognition Model with Deep Meta-Learning
(thesis abstract)
Mark de Blaauw
Diederik Roijers
Vesa Muhonen
Deep Learning Applied to Sign Language
(thesis abstract)
Jérôme Fink
Anthony Clève
Benoît Frénay
Demo Session
A Motorized Wheelchair that Learns to Make its Way through a Crowd
(demo abstract)
Denis Steckelmacher
Hélène Plisnier
Ann Nowé
A Virtual Maze Game to Explain Reinforcement Learning
(demo abstract)
Youri Coppens
Eugenio Bargiacchi
Ann Nowé
An Interactive Consultant
(demo abstract)
Pierre Carbonnelle
Bram Aerts
Marjolein Deryck
Joost Vennekens
Marc Denecker
Virtual Screening on FPGA
(demo abstract)
Tom Vander Aa
Tom Ashby
Roel Wuyts
DuStt – A Speech-to-Text Engine for Dutch
(demo abstract)
Willem Röpke
Roxana Rădulescu
Kyriakos Efthymiadis
Ann Nowé
Gesture Recognition with an FMCW Radar
(demo abstract)
Habib-ur-Rehman Khalid
Sofie Pollin
Thomas Gielen
Hans Cappelle
Miguel Glassée
André Bourdoux
Hichem Sahli
Multi-Agent Reinforcement Learning Tool for Job Shop Scheduling Problems
(demo abstract)
Jessica Coto Palacio
Yailen Martínez Jiménez
Ann Nowé
Interactive Learning of Grounded Concepts
(demo abstract)
Jens Nevens
Paul Van Eecke
Katrien Beuls
Politeness Detection in Speech for Human-Computer Interaction
(demo abstract)
Selma Yilmazyildiz Kayaarma
Sherik Lehal
Hichem Sahli
ZebraTutor: Explaining How to Solve Logic Grid Puzzles
(demo abstract)
Jens Claes
Bart Bogaerts
Rocsildes Canoy
Emilio Gamba
Tias Guns
2019-11-05: submitted by Nick Harley,
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