| 2023 | A GNN-Based Architecture for Group Detection from Spatio-Temporal Trajectory Data. Maedeh Nasri, Zhizhou Fang, Mitra Baratchi, Gwenn Englebienne, Shenghui Wang, Alexander Koutamanis, Carolien Rieffe |
| 2023 | A Similarity-Guided Framework for Error-Driven Discovery of Patient Neighbourhoods in EMA Data. Vishnu Unnikrishnan, Miro Schleicher, Clara Puga, Rüdiger Pryss, Carsten Vogel, Winfried Schlee, Myra Spiliopoulou |
| 2023 | AID4HAI: Automatic Idea Detection for Healthcare-Associated Infections from Twitter, a Framework Based on Active Learning and Transfer Learning. Zahra Kharazian, Mahmoud Rahat, Fábio F. Gama, Peyman Sheikholharam Mashhadi, Slawomir Nowaczyk, Tony Lindgren, Sindri Magnússon |
| 2023 | APs: A Proxemic Framework for Social Media Interactions Modeling and Analysis. Maxime Masson, Philippe Roose, Christian Sallaberry, Rodrigo Agerri, Marie-Noëlle Bessagnet, Annig Le Parc-Lacayrelle |
| 2023 | Advances in Intelligent Data Analysis XXI - 21st International Symposium on Intelligent Data Analysis, IDA 2023, Louvain-la-Neuve, Belgium, April 12-14, 2023, Proceedings Bruno Crémilleux, Sibylle Hess, Siegfried Nijssen |
| 2023 | An Investigation of Structures Responsible for Gender Bias in BERT and DistilBERT. Thibaud Leteno, Antoine Gourru, Charlotte Laclau, Christophe Gravier |
| 2023 | Contextual Word Embeddings Clustering Through Multiway Analysis: A Comparative Study. Mira Ait Saada, Mohamed Nadif |
| 2023 | Data-Centric Perspective on Explainability Versus Performance Trade-Off. Amirhossein Berenji, Slawomir Nowaczyk, Zahra Taghiyarrenani |
| 2023 | Diffusion Transport Alignment. Andrés F. Duque, Guy Wolf, Kevin R. Moon |
| 2023 | Discovering Diverse Top-K Characteristic Lists. Antonio Lopez-Martinez-Carrasco, Hugo Manuel Proença, Jose M. Juarez, Matthijs van Leeuwen, Manuel Campos |
| 2023 | Discovering Rule Lists with Preferred Variables. Ioanna Papagianni, Matthijs van Leeuwen |
| 2023 | Diverse Paraphrasing with Insertion Models for Few-Shot Intent Detection. Raphaël Chevasson, Charlotte Laclau, Christophe Gravier |
| 2023 | Don't Start Your Data Labeling from Scratch: OpSaLa - Optimized Data Sampling Before Labeling. Andraz Pelicon, Syrielle Montariol, Petra Kralj Novak |
| 2023 | Dropping Incomplete Records is (not so) Straightforward. Rianne Margaretha Schouten, Victoria Tascau, Gabriel G. Ziegler, Davide Casano, Marco Ardizzone, Michael-Angelos Erotokritou |
| 2023 | Effects of Locality and Rule Language on Explanations for Knowledge Graph Embeddings. Luis Galárraga |
| 2023 | Explaining Black Box Reinforcement Learning Agents Through Counterfactual Policies. Maria Movin, Guilherme Dinis Junior, Jaakko Hollmén, Panagiotis Papapetrou |
| 2023 | Explanations for Itemset Mining by Constraint Programming: A Case Study Using ChEMBL Data. Maksim Koptelov, Albrecht Zimmermann, Patrice Boizumault, Ronan Bureau, Jean Luc Lamotte |
| 2023 | Forecasting Electricity Prices: An Optimize Then Predict-Based Approach. Léonard Tschora, Erwan Pierre, Marc Plantevit, Céline Robardet |
| 2023 | GASTeN: Generative Adversarial Stress Test Networks. Luís Cunha, Carlos Soares, André Restivo, Luís F. Teixeira |
| 2023 | Geolet: An Interpretable Model for Trajectory Classification. Cristiano Landi, Francesco Spinnato, Riccardo Guidotti, Anna Monreale, Mirco Nanni |
| 2023 | LEMON: Alternative Sampling for More Faithful Explanation Through Local Surrogate Models. Dennis Collaris, Pratik Gajane, Joost Jorritsma, Jarke J. van Wijk, Mykola Pechenizkiy |
| 2023 | Learning Permutation-Invariant Embeddings for Description Logic Concepts. Caglar Demir, Axel-Cyrille Ngonga Ngomo |
| 2023 | Meta-learning for Automated Selection of Anomaly Detectors for Semi-supervised Datasets. David Schubert, Pritha Gupta, Marcel Wever |
| 2023 | Mind the Gap: Measuring Generalization Performance Across Multiple Objectives. Matthias Feurer, Katharina Eggensperger, Edward Bergman, Florian Pfisterer, Bernd Bischl, Frank Hutter |
| 2023 | On Compositionality in Data Embedding. Zhaozhen Xu, Zhijin Guo, Nello Cristianini |
| 2023 | On the Change of Decision Boundary and Loss in Learning with Concept Drift. Fabian Hinder, Valerie Vaquet, Johannes Brinkrolf, Barbara Hammer |
| 2023 | Online Influence Forest for Streaming Anomaly Detection. Inês Martins, João S. Resende, João Gama |
| 2023 | Out-of-Distribution Generalisation with Symmetry-Based Disentangled Representations. Loek Tonnaer, Mike Holenderski, Vlado Menkovski |
| 2023 | QBERT: Generalist Model for Processing Questions. Zhaozhen Xu, Nello Cristianini |
| 2023 | ROCKAD: Transferring ROCKET to Whole Time Series Anomaly Detection. Andreas Theissler, Manuel Wengert, Felix Gerschner |
| 2023 | Revised Conditional t-SNE: Looking Beyond the Nearest Neighbors. Edith Heiter, Bo Kang, Ruth Seurinck, Jefrey Lijffijt |
| 2023 | Shapley Values with Uncertain Value Functions. Raoul Heese, Sascha Mücke, Matthias Jakobs, Thore Gerlach, Nico Piatkowski |
| 2023 | Should We Consider On-Demand Analysis in Scale-Free Networks? Arnaud Soulet |
| 2023 | Spatial Graph Convolution Neural Networks for Water Distribution Systems. Inaam Ashraf, Luca Hermes, André Artelt, Barbara Hammer |
| 2023 | The Other Side of Compression: Measuring Bias in Pruned Transformers. Irina Proskurina, Guillaume Metzler, Julien Velcin |
| 2023 | Towards Data Science Design Patterns. Michael R. Berthold, Dashiell Brookhart, Schalk Gerber, Satoru Hayasaka, Maarit Widmann |
| 2023 | Transferable Deep Metric Learning for Clustering. Mohamed Alami Chehboune, Rim Kaddah, Jesse Read |
| 2023 | Translated Texts Under the Lens: From Machine Translation Detection to Source Language Identification. Massimo La Morgia, Alessandro Mei, Eugenio Nerio Nemmi, Luca Sabatini, Francesco Sassi |
| 2023 | User Authentication via Multifaceted Mouse Movements and Outlier Exposure. Jennifer Jorina Matthiesen, Hanne Hastedt, Ulf Brefeld |