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ORCID31st BNAIC / 28th BENELEARN 2019: Brussels, Belgium
- Katrien Beuls, Bart Bogaerts, Gianluca Bontempi, Pierre Geurts, Nick Harley, Bertrand Lebichot, Tom Lenaerts, Gilles Louppe, Paul Van Eecke:
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. CEUR Workshop Proceedings 2491, CEUR-WS.org 2019
ML1: Applied Machine Learning
- Théo Verhelst, Olivier Caelen, Jean-Christophe Dewitte, Bertrand Lebichot, Gianluca Bontempi:
Understanding Telecom Customer Churn with Machine Learning: From Prediction to Causal Inference. - Abel Díaz Berenguer, Meshia Cédric Oveneke, Mitchel Alioscha-Pérez, Hichem Sahli:
Paired Supervised Learning and Unsupervised Pretraining of CNN-Architecture for Violence Detection in Videos. - Paulo Roberto de Oliveira da Costa, Jason Rhuggenaath, Yingqian Zhang, Alp Akcay, Wan-Jui Lee, Uzay Kaymak:
Data-Driven Policy on Feasibility Determination for the Train Shunting Problem. - Alireza Gharahighehi, Celine Vens:
News Topic Recommendation Using an Extended Bayesian Personalized Ranking. - Pieter van den Ham, Bert Bredeweg, Maartje E. J. Raijmakers:
Analysing Visitor Flow Using a Bluetooth Positioning System.
ML2: Deep Learning
- Siamak Mehrkanoon:
Cross-Domain Neural-Kernel Networks. - José Oramas M., Kaili Wang, Tinne Tuytelaars:
Interpreting and Explaining Deep Models Visually. - Robin Manhaeve, Sebastijan Dumancic, Angelika Kimmig, Thomas Demeester, Luc De Raedt:
DeepProbLog: Neural Probabilistic Logic Programming. - Gabrielle Ras, Luca Ambrogioni, Umut Güçlü
, Marcel van Gerven:
Temporal Factorization of 3D Convolutional Kernels. - Nick Seeuws, Amir Hossein Ansari, Sabine Van Huffel, Gunnar Naulaers:
Unsupervised Deep Feature Extraction for Neonatal Sleep Stage Classification.
AI1: Constraint Programming
- Anna Louise D. Latour, Behrouz Babaki, Siegfried Nijssen:
Stochastic Constraint Propagation for Mining Probabilistic Networks. - Alex Mattenet, Ian Davidson, Siegfried Nijssen, Pierre Schaus:
Generic Constraint-Based Block Modeling Using Constraint Programming. - Hélène Verhaeghe, Siegfried Nijssen, Gilles Pesant, Claude-Guy Quimper, Pierre Schaus:
Learning Optimal Decision Trees Using Constraint Programming. - Rocsildes Canoy, Tias Guns:
Vehicle Routing by Learning from Historical Solutions.
RP1: Applied Machine Learning
- Mathias Van Herreweghe, Mathias Verbeke, Wannes Meert, Tom Jacobs:
A Machine Learning-Based Approach for Predicting Tool Wear in Industrial Milling Processes. - Valentin Hamaide, François Glineur:
Predictive Maintenance of a Rotating Condenser Inside a Synchrocyclotron. - Lars Bokkers, Luca Ambrogioni, Umut Güçlü:
Segmentation of Photovoltaic Panels in Aerial Photography Using Group Equivariant FCNs. - Xianghui Xie, Laurens Meeus, Aleksandra Pizurica:
Partial Convolution Based Multimodal Autoencoder for Art Investigation. - Pieter Delobelle, Bettina Berendt:
Time to Take Emoji Seriously: They Vastly Improve Casual Conversational Models. - Sinnu Susan Thomas, Jacopo Palandri, Mohsen Lakehal-Ayat, Punarjay Chakravarty, Friedrich Wolf-Monheim, Matthew B. Blaschko:
Designing MacPherson Suspension Architectures Using Bayesian Optimization. - Jens de Hoog, Siegfried Mercelis, Peter Hellinckx:
Improving Machine Learning-Based Decision-Making Through Inclusion of Data Quality. - Pierre Dagnely, Tom Tourwé, Elena Tsiporkova:
Industrial Assets Performance Labelling Based on Numerically Encoded Event Logs.
RP2: Applications of Artificial Intelligence
- Siamak Mehrkanoon:
Deep Shared Representation Learning for Weather Elements Forecasting. - Timothy Verstraeten, Ann Nowé, Jan Helsen:
Failure Avoidance for Wind Turbines through Fleetwide Control. - Silvia Tulli, Diego Agustín Ambrossio, Amro Najjar, Francisco Javier Rodríguez-Lera:
Great Expectations & Aborted Business Initiatives: The Paradox of Social Robot Between Research and Industry. - Mitchel Alioscha-Pérez, Meshia Cédric Oveneke, Abel Díaz Berenguer, Cédric Bertrand, Hichem Sahli:
End-To-End Anomaly Detection, Correction and Prediction of Missing Values in Historical Daily Temperature Timeseries. - Mostafa Dehghani, Hosein Azarbonyad, Jaap Kamps, Maarten de Rijke:
Learning to Transform, Combine, and Reason in Open-Domain Question Answering. - Cor Steging, Lambert Schomaker, Bart Verheij:
The XAI paradox: Systems that Perform Well for the Wrong Reasons. - Hamed Ayoobi, Ming Cao, Rineke Verbrugge, Bart Verheij:
Handling Unforeseen Failures Using Argumentation-Based Learning. - Nina Zizakic, Izumi Ito, Laurens Meeus, Aleksandra Pizurica:
Autoencoder-Learned Local Image Descriptor for Image Inpainting. - Damian Kurpiewski, Michal Knapik, Wojciech Jamroga:
On Domination and Control in Strategic Ability.
ML3: Applied ML & Machine Learning for Medicine
- Joris Roels, Yvan Saeys:
Cost-Efficient Segmentation of Electron Microscopy Images Using Active Learning. - Tom Van Steenkiste, Dirk Deschrijver, Tom Dhaene:
Disentangled Variational Auto-Encoders for Explaining ECG Beat Embeddings. - Maxim Lippeveld, Carly Knill, Emma Ladlow, Andrew Fuller, Louise J. Michaelis, Yvan Saeys, Andrew Filby, Daniel Peralta:
Classification of Human White Blood Cells Using Machine Learning for Stain-Free Imaging Flow Cytometry. - Tom Vander Aa, Imen Chakroun, Tom Ashby, Jaak Simm, Adam Arany, Yves Moreau, Thanh Le Van, José Felipe Golib Dzib, Jörg K. Wegner, Vladimir I. Chupakhin, Hugo Ceulemans, Roel Wuyts, Wilfried Verachtert:
SMURFF: A High-Performance Framework for Matrix Factorization Methods. - Marijn van Wingerden, Jelle de Boer, Eric O. Postma:
Predicting 120-Day Hospital Readmission Using Medical Administrative Patient Data.
AI2: AI For Health & Medicine
- Pieter Libin, Nassim Versbraegen, Ana B. Abecasis, Perpetua Gomes, Tom Lenaerts, Ann Nowé:
Towards a Phylogenetic Measure to Quantify HIV Incidence. - Anne-Ruth José Meijer, Arnoud Visser:
A Residual Neural-Network Model to Predict Visual Cortex Measurements. - Sarah Itani, Fabian Lecron, Philippe Fortemps:
Data Mining for ADHD & ASD Prediction Based on Resting-State fMRI Signals: A Literature Review. - Emmeke Veltmeijer, Sezer Karaoglu, Theo Gevers:
Integrating Clinically-Relevant Features into Skin Lesion Classification.
ML4: Supervised & Semi-Supervised Learning
- Guillaume Derval, Frédéric Docquier, Pierre Schaus:
An Aggregate Learning Approach for Interpretable Semi-Supervised Population Prediction and Disaggregation Using Ancillary Data. - Thomas Mortier, Marek Wydmuch, Krzysztof Dembczynski, Eyke Hüllermeier, Willem Waegeman:
Set-Valued Prediction in Multi-Class Classification. - Jonathan Peck, Bart Goossens, Yvan Saeys:
Calibrated Multi-Probabilistic Prediction as a Defense against Adversarial Attacks. - Mengzi Tang, Raúl Pérez-Fernández, Bernard De Baets:
Machine Learning Methods for Ordinal Classification with Additional Relative Information.
AI3: Generative & Creative AI
- Frederik Calsius, Stylianos Asteriadis:
Synthesizing Personality-Dependent Body Postures Using Generative Adversarial Networks. - David Winant, Joachim Schreurs, Johan A. K. Suykens:
Latent Space Exploration Using Generative Kernel PCA. - Thomas Winters:
Modelling Mutually Interactive Fictional Character Conversational Agents. - Steven Homer:
Learning Hierarchical Spectral Representations of Human Speech with the Information Dynamics of Thinking. - Cátia Ferreira, Sviatlana Hoehn:
Crafting Conversational Agents' Personality in a User-Centric Context. - René Raab, Kurt Driessens:
A Generative Policy Gradient Approach for Learning to Play Text-Based Adventure Games.
AI4: Natural Language
- Willem Röpke, Roxana Radulescu, Kyriakos Efthymiadis, Ann Nowé:
Training a Speech-to-Text Model for Dutch on the Corpus Gesproken Nederlands. - Florian Kunneman, Thiago Castro Ferreira, Antal van den Bosch, Emiel Krahmer:
Question Similarity in Community Question Answering: A Systematic Exploration of Preprocessing Methods and Models. - Wietse de Vries:
Explaining Lexical Processing Times with Cognitively Plausible Computational Models. - Zoe Gerolemou, Johannes C. Scholtes:
Target-Based Sentiment Analysis as a Sequence-Tagging Task.
RP3: Reinforcement Learning
- Denis Steckelmacher, Hélène Plisnier, Diederik M. Roijers, Ann Nowé:
Sample-Efficient Model-Free Reinforcement Learning with Off-Policy Critics. - Oliver Roesler, Ann Nowé:
Action Learning and Grounding in Simulated Human-Robot Interactions. - Reza Refaei Afshar, Yingqian Zhang, Murat Firat, Uzay Kaymak:
A Reinforcement Learning Method to Select Ad Networks in Waterfall Strategy. - Hélène Plisnier, Denis Steckelmacher, Diederik M. Roijers, Ann Nowé:
Transfer Reinforcement Learning across Environment Dynamics with Multiple Advisors. - Steven Homer:
Maximum Entropy Bayesian Actor Critic. - Pieter Libin, Timothy Verstraeten, Diederik M. Roijers, Wenjia Wang, Kristof Theys, Ann Nowé:
Thompson Sampling for m-top Exploration. - Arne Gevaert, Jonathan Peck, Yvan Saeys:
Distillation of Deep Reinforcement Learning Models Using Fuzzy Inference Systems.
RP4: Machine Learning for Bioinformatics & Life Science
- Redona Brahimetaj, Evgenia Papavasileiou, Frederik Temmermans, Bruno Cornelis, Inneke Willekens, Johan de Mey, Bart Jansen:
Computer Aided Detection and Diagnosis System for Breast Cancer Detection Based on High Resolution 3D micro-CT Breast Microcalcifications. - Christina Papagiannopoulou, René Parchen, Willem Waegeman:
Investigating Time Series Classification Techniques for Rapid Pathogen Identification with Single-Cell MALDI-TOF Mass Spectrum Data. - Jiangming Sun, Nina Jeliazkova, Vladimir I. Chupakhin, José Felipe Golib Dzib, Lars Carlsson, Jörg K. Wegner, Hugo Ceulemans, Ivan Georgiev, Vedrin Jeliazkov, Nikolay T. Kochev, Thomas J. Ashby, Hongming Chen:
ExCAPE-DB: An Integrated Large Scale Dataset Facilitating Big Data Analysis in Chemogenomics. - Fateme Nateghi Haredasht, Mohammad Hassan Moradi:
Nonlinear Causality Inference in Microarray Time Series. - Aren Maes, Tom Van Steenkiste, Tom Dhaene, Dirk Deschrijver:
A Study of Early Sepsis Detection Models Based on Multivariate Medical Time Series.
ML5: Deep Learning & Reinforcement Learning
- Matthia Sabatelli, Gilles Louppe, Pierre Geurts, Marco A. Wiering:
Deep Quality-Value (DQV) Learning. - Sammie Katt, Frans A. Oliehoek, Chris Amato:
Bayesian RL in Factored POMDPs. - Jakob Struye, Kevin Mets, Steven Latré:
HTMRL: Biologically Plausible Reinforcement Learning with Hierarchical Temporal Memory. - Antoine Wehenkel, Gilles Louppe:
Unconstrained Monotonic Neural Networks.
ML6: Data & Network Mining
- Bo Kang, Jefrey Lijffijt, Tijl De Bie:
Conditional Network Embeddings. - Giannis Bekoulis, Johannes Deleu, Thomas Demeester, Chris Develder:
Adversarial Perturbations for Joint Entity and Relation Extraction. - Joachim Schreurs, Michaël Fanuel, Johan A. K. Suykens:
Towards Deterministic Diverse Subset Sampling. - Joey De Pauw, Sandy Moens, Bart Goethals:
SubSect - An Interactive Itemset Visualization.
AI5: Knowledge Representation & Hybrid AI
- Frank van Harmelen, Annette ten Teije:
A Boxology of Design Patterns for Hybrid Learning and Reasoning Systems. - Sicco Verwer, Yingqian Zhang:
Learning Optimal Classification Trees Using a Binary Linear Program Formulation. - Matthias van der Hallen, Gerda Janssens:
SOGrounder: Modelling and Solving Second-Order Logic. - Simon Vandevelde, Kylian Van Dessel, Herman Crauwels:
An Interactive Knowledge Base Application for Group Assignment. - Andrei Popescu, Pinar Yolum:
PARCo: A Knowledge-Based Agent for Context-Sensitive Reasoning and Decision-Making Regarding Privacy.
RP5: Supervised & Semi-Supervised Learning, Classification
- Jasper Paalman, Shantanu Mullick, Kalliopi Zervanou, Yingqian Zhang:
Term Based Semantic Clusters for Very Short Text Classification. - Nienke Eijsvogel, Marijn Schraagen:
Revision Classification for Current Events in Dutch Wikipedia Using a Long Short-Term Memory Network. - Marilyn Bello, Gonzalo Nápoles, Koen Vanhoof, Rafael Bello:
Reduction Methods for Multi-Label Datasets Based on Granular Computing. - Dimitri Papadimitriou, Steven Latré:
Scientific Machine Learning: Towards Predictive Closed-Form Models. - Dave R. Stikkolorum, Peter van der Putten, Caroline Sperandio, Michel Chaudron:
Towards Automated Grading of UML Class Diagrams with Machine Learning. - Felipe Kenji Nakano, Ricardo Cerri:
Hierarchical Classification of Transposable Elements.
RP6: Agents & Multi-Agent Systems
- Onuralp Ulusoy, Pinar Yolum:
Privacy Norms in Online Social Networks. - Merijn Bruijnes, Siska Fitrianie, Deborah Richards, Amal Abdulrahman, Willem-Paul Brinkman:
What are we Measuring Anyway? A Literature Survey of Questionnaires Used in Studies Reported in the Intelligent Virtual Agent Conferences. - Jannick Hemelhof, Mihail Mihaylov, Ann Nowé:
Improving Zero-Intelligence Plus for Call Markets.
BS1: Best Student Papers
- Jelmer Neeven:
Iterative Model-Based Transfer in Deep Reinforcement Learning. - Rémi Delanghe, Tom Van Steenkiste, Dirk Deschrijver, Tom Dhaene:
Continuous Exploitative Measurement Trajectories Using Bayesian Optimisation. - Kevin Bardool, Tinne Tuytelaars, José Oramas M.:
A Context Aware Deep Learning Architecture for Object Detection. - Regis Loeb, Timothy Verstraeten, Ann Nowé, Ann Dooms:
Privacy Preserving Reinforcement Learning over Distributed Datasets. - Nikki Theeuwes, Geert-Jan van Houtum, Yingqian Zhang, Björn Gadet:
Formalization and Improvement of Ambulance Dispatching in Brabant-Zuidoost. - Gang Wang, Bernard De Baets:
Automated Artemia Detection and Length Measurement Using Deep Convolutional Networks.
AI6: Multi-Agent Systems
- Jonas Kuckling, Keneth Ubeda Arriaza, Mauro Birattari:
Simulated Annealing as an Optimization Algorithm in the Automatic Modular Design of Robot Swarms. - Davide Dell'Anna, Mehdi Dastani, Fabiano Dalpiaz:
Runtime Revision of Norms and Sanctions Based on Agent Preferences. - Gaëtan Spaey, Miquel Kegeleirs, David Garzón-Ramos, Mauro Birattari:
Comparison of Different Exploration Schemes in the Automatic Modular Design of Robot Swarms.
AI7: Explainability
- Hanna Schraffenberger, Yana van de Sande, Gabi Schaap, Tibor Bosse:
Investigating People's Attitudes Towards AI with a Smart Photo Booth. - Nico Roos, Zhenglong Sun:
Explainable Robotics Applied to Bipedal Walking Gait Development. - Michelle Peters, Lindsay Kempen, Meike Nauta, Christin Seifert:
Visualising the Training Process of Convolutional Neural Networks for Non-Experts.
RP7: Deep Learning
- Gilles Louppe, Joeri Hermans, Kyle Cranmer:
Adversarial Variational Optimization of Non-Differentiable Simulators. - Kevin Bardool, Tinne Tuytelaars, José Oramas M.:
A Systematic Analysis of a Context Aware Deep Learning Architecture for Object Detection. - Mark de Blaauw, Diederik M. Roijers, Vesa Muhonen:
A Scalable Logo Recognition Model with Deep Meta-Learning. - Jérôme Fink, Anthony Cleve, Benoît Frénay:
Deep Learning Applied to Sign Language.
Demo Session
- Denis Steckelmacher, Hélène Plisnier, Ann Nowé:
A Motorized Wheelchair that Learns to Make its Way through a Crowd. - Youri Coppens, Eugenio Bargiacchi, Ann Nowé:
A Virtual Maze Game to Explain Reinforcement Learning. - Pierre Carbonnelle, Bram Aerts, Marjolein Deryck, Joost Vennekens, Marc Denecker:
An Interactive Consultant. - Tom Vander Aa, Tom Ashby, Roel Wuyts:
Virtual Screening on FPGA. - Willem Röpke, Roxana Radulescu, Kyriakos Efthymiadis, Ann Nowé:
DuStt - A Speech-to-Text Engine for Dutch. - Habib-Ur-Rehman Khalid, Sofie Pollin, Thomas Gielen, Hans Cappelle, Miguel Glassée, André Bourdoux, Hichem Sahli:
Gesture Recognition with an FMCW Radar. - Jessica Coto Palacio, Yailen Martínez Jiménez, Ann Nowé:
Multi-Agent Reinforcement Learning Tool for Job Shop Scheduling Problems. - Jens Nevens, Paul Van Eecke, Katrien Beuls:
Interactive Learning of Grounded Concepts. - Selma Yilmazyildiz Kayaarma, Sherik Lehal, Hichem Sahli:
Politeness Detection in Speech for Human-Computer Interaction. - Jens Claes, Bart Bogaerts, Rocsildes Canoy, Emilio Gamba, Tias Guns:
ZebraTutor: Explaining How to Solve Logic Grid Puzzles.
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