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Accepted Submissions

Type A: Regular Papers

Original work that advances Artificial Intelligence and Machine Learning.

Author(s) Title
Jef Plochaet and Toon Goedemé Towards Automatic Proctoring of Online Exams Using Video Anomaly Detection
Paul Wallbott, Sascha Grollmisch and Thomas Köllmer Examining speaker and keyword uniqueness: Partitioning keyword spotting datasets for federated learning with the largest differencing method
Thomas Cassimon, Liam Hertoghs, Simon Vanneste, Phil Reiter, Kevin Mets, Tom De Schepper, Siegfried Mercelis and Peter Hellinckx Predicting Image Classifier Performance Using the Synthetic Petri Dish Method
Britt Schmitz and Marc Ponsen Change Detection of Land Use: A Deep Learning Case-Study
Tobias Glasmachers Recipe for Fast Large-scale SVM Training: Polishing, Parallelism, and more RAM!
Wai Wong, Walter Schaeken and Joost Vennekens On the importance of experimental psychology for explainable artificial intelligence
Arnon Vandenberghe, Lyse Naomi Wamba Momo, Vincent Scheltjens and Bart De Moor Multimodal Deep Learning for Early Length of Stay Prediction using Patient Similarity Embeddings
Daimy Van Caudenberg and Bart Bogaerts Static Symmetry and Dominance Breaking for Pseudo-Boolean Optimization
Astrid Vanneste, Thomas Somers, Simon Vanneste, Kevin Mets, Tom De Schepper, Siegfried Mercelis and Peter Hellinckx Scalability of Message Encoding Techniques for Continuous Communication Learned with Multi-Agent Reinforcement Learning
Pierre Carbonnelle, Simon Vandevelde, Joost Vennekens and Marc Denecker IDP-Z3: a reasoning engine for FO(.)
Elena Congeduti and Frans Oliehoek A Cross-Field Review of State Abstraction for Markov Decision Processes
Jean Dessain Improving the prediction of asset returns with machine learning by using a custom loss function
Marco Loog and Tom Viering A Survey of Learning Curves with Bad Behavior: or How More Data Need Not Lead to Better Performance
Luc Steels and Lara Verheyen Quantifying the contribution of different knowledge sources in text understanding
Rodi Laanen, Maedeh Nasri, Richard van Dijk, Mitra Baratchi, Alexander Koutamanis and Carolien Rieffe Automated classification of pre-defined movement patterns: A comparison between GNSS and UWB technology
Isel Grau, Michiel de Hoop, Ana Glaser, Gonzalo Nápoles and Remco Dijkman Semiconductor Demand Forecasting using Long Short-term Cognitive Networks
Yochem van Rosmalen, Florian van der Steen, Sebastiaan Jans and Daan van der Weijden Bursting the Burden Bubble? An Assessment of Sharma et al.’s Counterfactual-Based Fairness Metric
Stijn Rotman and Boris Čule Forecasting Electric Vehicle Supply Equipment Availability
Victoria Catalán Pastor, Elena Congeduti, Aleksander Czechowski and Frans A. Oliehoek Overcoming Traffic Sensors Malfunctions with Deep Learning
Zhiyi Chen, Marco Loog and Jesse H. Krijthe Explaining Two Strange Learning Curves
Ozgur Taylan Turan, David M.J. Tax and Marco Loog When MAML Learns Quickly, Does It Generalize Well?
Suzana Bašić, Marcio Fuckner and Pascal Wiggers Explainable Misinformation Detection from Text: A Critical Look
Sander van Donkelaar, Lois Daamen, Paul Andel, Ralf Zoetekouw and Sharon Ong Superpixel-based Context Restoration for Self-supervised Pancreas Segmentation from CT scans
Merlijn Krale, Thiago Simão and Nils Jansen The Value of Measuring in Q-learning for Markov Decision Processes
Rastislav Hronsky and Emmanuel Keuleers Does the Choice of a Segmentation Algorithm Affect the Performance of Text Classifiers?
Carla Wrede, Mark Winands and Anna Wilbik Linguistic Summaries as Explanation Mechanism for Classification Problems
Raphaela Butz, Arjen Hommersom, Marco Barenkamp and Hans van Ditmarsch One counterfactual does not make an explanation
Gadzhi Musaev, Kevin Mets, Tom De Schepper, Peter Hellinckx, Rokas Tamošiūnas and Vadim Uvarov On-Device Deep Learning Location Category Inference Model
Johan Kwisthout Expanding Bayesian networks
Arya Tri Prabawa, Merel Jung, Kostas Stoitsas, Werner Liebregts and Itır Önal Ertuğrul Predicting Probability of Investment Based on Investor’s Facial Expression in a Startup Funding Pitch
Deniz Ezgi Kurt and Egberdien van der Peijl Is this art? A trans-disciplinary study of metadata in AI using the categorisation of 'artists' writing’ coined by the Art and Language Group (1968 - ).
Kshitij Goyal, Wannes Meert, Hendrik Blockeel, Elia Van Wolputte, Koen Vanderstraeten, Wouter Pijpops and Kurt Jaspers Automatic Generation of Product Concepts from Positive Examples, with an Application to Music Streaming
Nico Roos Specificity and context dependent preferences in argumentation systems
Paul Keuren, Marc Ponsen and Ayoub Bagheri WordGraph2Vec: Combining domain knowledge with embeddings
Louis Bagot, Kevin Mets, Tom De Schepper and Steven Latré A Case for Feature-Based Successor Features for Transfer in Reinforcement Learning
Matthias Hutsebaut-Buysse, Kevin Mets, Tom De Schepper and Steven Latre Structured Exploration Through Instruction Enhancement for Object Navigation
Thi Hoang Anh Tran, Malina Lara Wiesner and Maurice van Keulen Influence of discretization granularity on learning classification models
Yuko Kato, David Tax and Marco Loog A view on model misspecification in uncertainty quantification
Ya Song, Laurens Bliek and Yingqian Zhang Algorithm Selection for Traveling Salesman Problem with Simplified PointNet++
Abdo Abouelrous, Yingqian Zhang and Laurens Bliek Digital Twin Applications in Urban Logistics: An Overview
Rolf Starre, Marco Loog and Frans Oliehoek Model-Based Reinforcement Learning with State Abstraction: A Survey
Joseph Mietkiewicz and Anders Madsen Improvement of the fine tuning algorithm for naïve Bayes
Gianluca Bontempi Between accurate prediction and poor decision making: the AI/ML gap (position paper)
Salima Lamsiyah and Christoph Schommer A Comparative Study of Sentence Embeddings for Unsupervised Extractive Multi-Document Summarization

Type B: Encores

Already published work in any AI/ML conference or journal.

Author(s) Title
Menno Oudshoorn, Timo Koppenberg and Neil Yorke-Smith Optimisation of Annual Planned Rail Maintenance (Article Abstract)
Daniel Daza, Michael Cochez and Paul Groth SlotGAN: Detecting Mentions in Text via Adversarial Distant Learning
Benjamin Rombaut, Joris Roels and Yvan Saeys BioSegment: Active Learning segmentation for 3D electron microscopy imaging
Romana Pernisch, Daniele Dell'Aglio, Mirko Serbak, Rafael Gonçalves and Abraham Bernstein Visualising the Effects of Ontology Changes and Studying their Understanding with ChImp
Florent Delgrange, Ann Nowé and Guillermo A. Pérez Distillation of RL Policies with Formal Guarantees via Variational Abstraction of Markov Decision Processes
Ksenija Stepanovic, Jichen Wu, Rob Everhardt and Mathijs de Weerdt Unlocking the Flexibility of District Heating Pipeline Energy Storage with Reinforcement Learning
Alejandro Morales-Hernández, Gonzalo Nápoles, Agnieszka Jastrzębska, Yamisleydi Salgueiro Sicilia and Koen Vanhoof Online learning of windmill time series using Long Short-term Cognitive Networks
Bojian Yin, Federico Corradi and Sander Bohte Accurate and efficient time-domain classification with adaptive spiking recurrent neural networks
Emre Erdogan, Frank Dignum, Rineke Verbrugge and Pinar Yolum Computational Theory of Mind for Human-Agent Collaboration
Sho Cremers, Valentin Robu, Daan Hofman, Titus Naber, Kawin Zheng and Sonam Norbu Efficient Methods for Approximating the Shapley Value for Asset Sharing in Energy Communities (Encore Abstract)
Grigory Neustroev, Sytze Andringa, Remco Verzijlbergh and Mathijs de Weerdt Deep Reinforcement Learning for Active Wake Control
Steven Michiels, Lynn Houthuys, Cédric De Schryver, Frederik Vogeler and Frederik Desplentere Machine learning for automated quality control in injection moulding manufacturing
Floris Geerts, Jasper Steegmans and Jan Van den Bussche On the expressive power of message-passing neural networks as global feature map transformers
Dimitrios Iliadis, Bernard De Baets and Willem Waegeman DeepMTP: a Python-based deep learning framework for multi-target prediction
Nele Albers, Mark A. Neerincx, Kristell M. Penfornis and Willem-Paul Brinkman Using a Virtual Coach to Quit Smoking: 14 Themes for User Needs
Azqa Nadeem and Sicco Verwer SECLEDS: Sequence Clustering in Evolving Data Streams via Multiple Medoids and Medoid Voting (Encore abstract)
Dimitrios Alivanistos, Max Berrendorf, Michael Cochez and Michael Galkin Query Embedding on Hyper-Relational Knowledge Graphs
Conor F Hayes, Timothy Verstraeten, Diederik M. Roijers, Enda Howley and Patrick Mannion Expected scalarised returns dominance: a new solution concept for multi-objective decision making
Loan Ho, Somjit Arch-Int, Erman Acar, Stefan Schlobach and Ngamnij Arch-Int An Argumentative Approach for Handling Inconsistency in Prioritized Datalog± Ontologies
Thomas Mortier, Eyke Hüllermeier, Krzysztof Dembczyński and Willem Waegeman Set-valued prediction in hierarchical classification
Oliver Urs Lenz, Daniel Peralta and Chris Cornelis Optimised one-class classification performance
Nicolas Dewolf, Bernard De Baets and Willem Waegeman Valid prediction intervals for regression problems
Felix Mohr, Tom Viering, Marco Loog and Jan van Rijn LCDB 1.0: An Extensive Learning Curves Database for Classification Tasks
Jeska Buhmann, Maxime De Bruyn, Ehsan Lotfi and Walter Daelemans Domain- and Task-Adaptation for VaccinChatNL, a Dutch COVID-19 FAQ Answering Corpus and Classification Model
Afsana Khan, Marijn ten Thij and Anna Wilbik Communication-Efficient Vertical Federated Learning
Floris den Hengst, Vincent François-Lavet, Mark Hoogendoorn and Frank van Harmelen Reinforcement Learning with Option Machines
Michiel van der Meer, Catholijn Jonker and Pradeep Kumar Murukannaiah HyEnA: Hybrid Intelligence for Argument Mining
Bert Bredeweg and Marco Kragten Requirements and challenges for hybrid intelligence: A case-study in education
Daniël Vos and Sicco Verwer Robust Optimal Classification Trees against Adversarial Examples
Arne Gevaert and Yvan Saeys PDD-SHAP: Fast Approximations for Shapley Values using Functional Decomposition
Konstantinos Theodorakos, Mauricio Agudelo, Joachim Schreurs, Johan Suykens and Bart De Moor Ozone forecasting across Belgium with co-evolutionary Neural Architecture Search
Conor F Hayes, Roxana Radulescu, Eugenio Bargiacchi, Johan Källström, Matthew Macfarlane, Mathieu Reymond, Timothy Verstraeten, Luisa M Zintgraf, Richard Dazeley, Fredrik Heintz, Enda Howley, Athirai A. Irissappane, Patrick Mannion, Ann Nowé, Gabriel Ramos, Marcello Restelli, Peter Vamplew and Diederik M. Roijers Abstract: A Practical Guide to Multi-Objective Reinforcement Learning and Planning
Jens Nevens, Jonas Doumen, Paul Van Eecke and Katrien Beuls Language Acquisition through Intention Reading and Pattern Finding

Type C: Demonstrations

Demonstrations of AI/ML applications.

Author(s) Title
Simon Vandevelde and Joost Vennekens FOLL-E: Teaching First Order Logic to Children
Daphne Lenders and Toon Calders A New Benchmarking Dataset for Fair ML
Marcio Fuckner, Suzana Bašić, Pascal Wiggers, Yuri Westplat, Rick van Kersbergen and Iman Firouzifard BubbleMachine: An agent-based modelling tool to analyse the interplay between cognitive preferences, social network interactions and algorithmic curation
Willem Röpke, Samuele Pollaci, Bram Vandenbogaerde, Jiahong Li and Youri Coppens Multi-Objective Scheduling for Agricultural Interventions
Tias Guns, Milan Pesa, Maxime Mulamba, Ignace Bleukx, Emilio Gamba and Senne Berden Sudoku Assistant - An AI-powered app to help solve pen-and-paper Sudokus
Ruben Janssens, Thomas Demeester and Tony Belpaeme Visual Conversation Starters for Human-Robot Interaction
Jeff van de Kamer, Maaike Hovenkamp, Erik Puik and Diederik M. Roijers Monitoring Diabetic Foot Ulceration Treatment with Smart Insoles and Neural Networks
Lucas N. Alegre, Florian Felten, El-Ghazali Talbi, Grégoire Danoy, Ann Nowé, Ana L. C. Bazzan and Bruno C. da Silva MO-Gym: A Library of Multi-Objective Reinforcement Learning Environments
Matthias Müller-Brockhausen and Hélène Plisnier Transferring While Playing the RL Agent
Axel Abels, Elias Fernández Domingos, Tom Lenaerts, Vito Trianni and Ann Nowé Bias Mitigation in Decision-Making with Expert Advice

Type D: Theses

Bachelor and Master theses.

Author(s) Title
Yawen Zhao and Jordy Van Landeghem Better Late than Never: Late Fusion Techniques for Document Classification
Fieke Middelraad This laptop has great coffee: Training a Dutch ABSA model from customer reviews
Erinn Van der Sande, Nick Harley and Geraint Wiggins Fabula Generation with BCDI Characters and Narrative Tension
Rickard K.A. Karlsson, Martin Willbo and Fredrik D. Johansson Learning using Privileged Time-Series
Donghwi Kim and Tom Viering Different approaches to fitting and extrapolating the learning curve
Liesbet De Vos Human-Interpretable Grounded Language Processing
Issa Hanou, Mathijs de Weerdt and Jesse Mulderij Applying the Pebble Motion problem: studying the feasibility of the Train Unit Shunting Problem
Wolf De Wulf Transfer learning in Brain-Computer Interfaces: Language-Pretrained Transformers for Classifying Electroencephalography
Dorian Vandenthoren Nonnegative Bilinear Matrix Factorization
Nikolaos Efthymiou and Neil Yorke-Smith Machine Learning for the Cyclic Hoist Scheduling Problem
Marlon Saelens, Marie-Francine Moens, Ruben Cartuyvels and Liesbeth Allein Implicit Reasoning over Temporal Relations in Evidence-Based Fact-Checking
Cédric Goemaere, Thomas Demeester, Tim Verbelen, Bart Dhoedt and Cedric De Boom Efficient Keyword Generation using Pretrained Language Models
Lin de Huybrecht, Nick Harley and Geraint Wiggins Text Rendering for Automatic Story Generation
Robbe Claeys, Yuju Ahn, Moobeom Hong, Inkyun Park and Jihwan Lim Towards a Systematic Investigation of Deep Learning Approaches for Bacterial Taxonomic Classification Using the 16S rRNA Gene
Seppe Renty, Raphaël Avalos, Andries Rosseau and Ann Nowé Tackling Scheduling Problems With Graph Structured Reinforcement Learning.
Prajit Bhaskaran and Tom Viering To Tune or not to Tune: Hyperparameter Influence on the Learning Curve
Idries Nasim and Shuai Wang Examining the Evolution of Identity graphs Through Redirection
Daan Van Wesenbeeck, Aras Yurtman, Wannes Meert and Hendrik Blockeel Unsupervised extraction and clustering of physical therapy exercise executions
William Dumez, Simon Vandevelde and Joost Vennekens Step-wise Explanations of Sudokus using IDP
Julius Wagenbach and Matthia Sabatelli Factors of Influence of the Overestimation Bias of Q-Learning
Tianyang Lu, Shuai Wang and Zhisheng Huang Towards Smart Urban Resilience: A Linked Data Approach
Shashank Subramanya and Gerasimos Spanakis MultiTM: A Multilingual Topic Modeling approach based on Clustering
Jeanine-Estelle Vallecalle Overview of psychometric tools to evaluate robotic creativity – A scoping review
Santiago Amaya Modelling of human behaviour in traffic interactions using Inverse Reinforcement Learning
Marnix Verduyn Comic Art Generation using GANs
Ethelbert Uzodinma and Jennifer Spenader Improving Domain Robustness in Out-of-Domain Corpus
Wim Fyen, Wannes Meert, Bart Thijs and Koenraad Debackere Investigation of the predictive power of the human capital of academic researchers on their financial performance using social network analysis and decision trees
Marius Sommerfeld, András Tóth, Stefan Schwartz, Joël Karel and Mirela Popa 3D Plant Segmentation for High Throughput Phenotyping using 3D Morphological Algorithms
Sander Brinkhuijsen, Romana Pernisch, Eljo Haspels and Mark Van Staalduinen Context-Aware Feature Vectors in Dark Web Page Classification
Roan Schellingerhout, Volodymyr Medentsiy and Maarten Marx Explainable Career Path Predictions using Neural Models
Willem Röpke, Diederik M. Roijers, Roxana Rădulescu and Ann Nowé Communication In Multi-Objective Games