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ORCID23rd IDA 2025: Konstanz, Germany
- Georg Krempl
, Kai Puolamäki, Ioanna Miliou:
Advances in Intelligent Data Analysis XXIII - 23rd International Symposium on Intelligent Data Analysis, IDA 2025, Konstanz, Germany, May 7-9, 2025, Proceedings. Lecture Notes in Computer Science 15669, Springer 2025, ISBN 978-3-031-91397-6
Applications of Data Science
- Dorra Sassi, Constance Thierry, David Gross-Amblard:
Credal Knowledge Tracing for Imprecise and Uncertain MCQ. 3-16 - Bouke L. Scheltinga, Jasper Reenalda, Jaap H. Buurke, Joost N. Kok:
Development of Models to Quantify Training Load in Outdoor Running Using Inertial Sensors. 17-27 - Bastien Mollet, Paul Ahavi, Antoine Cornuéjols, Jean-Loup Faulon, Evelyne Lutton, Alberto Tonda:
Estimating the Learning Capacity of Bacterial Metabolic Networks. 28-40 - Anne Rother, Till Ittermann, Myra Spiliopoulou:
Semi-supervised Learning with Pairwise Instance Comparisons for Medical Instance Classification. 41-53 - Ariel Basso Madjoukeng, Kenmogne Edith Belise, Pierre Poitier, Benoît Frénay, Jérôme Fink:
Local-Global Data Augmentation for Contrastive Learning in Static Sign Language Recognition. 54-66 - Maedeh Nasri, Mitra Baratchi, Alexander Koutamanis, Carolien Rieffe:
SiamCircle: Trajectory Representation Learning in Free Settings. 67-80 - G. Charbel N. Kindji, Elisa Fromont, Lina Maria Rojas-Barahona, Tanguy Urvoy:
Synthetic Tabular Data Detection in the Wild. 81-96 - Canberk Ozen, Slawomir Nowaczyk, Prayag Tiwari, Sepideh Pashami:
Assessing the Graph Structure Learning in Graph Deviation Networks. 97-109
Foundations of Data Science
- Loren Nuyts, Jesse Davis:
The When and How of Target Variable Transformations. 113-126 - Mateusz Zarski, Slawomir Nowaczyk:
Balancing Performance and Scalability of Demand Forecasting ML Models. 127-140 - Tsuyoshi Yamashita, Kunitake Kaneko:
Balancing Global Importance and Source Proximity for Personalized Recommendations Using Random Walk Length. 141-153 - Marco Loog, Jesse H. Krijthe, Manuele Bicego:
Counterintuitive Behavior of Clustering Quality: Findings for K-Means on Synthetic and Real Data. 154-166 - Lise Kastner, Bertrand Cuissart, Jean Luc Lamotte:
BOWSA: A Contribution of Sensitivity Analysis to Improve Bayesian Optimization for Parameter Tuning. 167-180 - Sietse Schröder, Mitra Baratchi, Jan N. van Rijn:
Overfitting in Combined Algorithm Selection and Hyperparameter Optimization. 181-194 - Carl Vico Heinrich, Tommie Lombarts, Jules Mallens, Luc Tortike, David Wolf, Wouter Duivesteijn:
Local Subgroup Discovery on Attributed Network Graphs. 195-208 - Soroush Ghandi, Benjamin Quost, Cassio de Campos:
Imposing Constraints in Probabilistic Circuits via Gradient Optimization. 209-220
Natural Language Processing
- Johannes Schneider:
Improving Next Tokens via Second-to-Last Predictions with Generate and Refine. 223-233 - Benoît Ronval, Pierre Dupont, Siegfried Nijssen:
Detection of Large Language Model Contamination with Tabular Data. 234-245 - Noor Khalal, Abdallah Alaa-Eddine Djamai, Imed Keraghel, Mohamed Nadif:
Imbalanced Data Clustering via Targeted Data Augmentation Using GMM and LLM. 246-260 - Bojan Cestnik, Andrej Kastrin, Boshko Koloski, Nada Lavrac:
Make Literature-Based Discovery Great Again Through Reproducible Pipelines. 261-273 - Clémence Sebe, Sarah Cohen-Boulakia, Olivier Ferret, Aurélie Névéol:
Extracting Information in a Low-Resource Setting: Case Study on Bioinformatics Workflows. 274-287 - Vu Minh Hoang Dang, Rakesh M. Verma:
Vocabulary Quality in NLP Datasets: An Autoencoder-Based Framework Across Domains and Languages. 288-301
Temporal and Streaming Data
- Stijn J. Rotman, Gianluca Guglielmo, Boris Cule, Michal Klincewicz:
Expertise Prediction of Tetris Players Using Eye Tracking Information. 305-317 - Julian Vexler, Björn Vieten, Martin Nelke, Stefan Kramer:
Integrating Inverse and Forward Modeling for Sparse Temporal Data from Sensor Networks. 318-329 - Daniel Persson, William Wahlberg, Anna Vettoruzzo, Slawomir Nowaczyk:
Bridging Spatial and Temporal Contexts: Sparse Transfer Learning. 330-342 - Ricardo Inácio, Vítor Cerqueira, Marília Barandas, Carlos Soares:
Meta-learning and Data Augmentation for Stress Testing Forecasting Models. 343-357 - Nuwan Gunasekara, Slawomir Nowaczyk, Sepideh Pashami:
Pragmatic Paradigm for Multi-stream Regression. 358-372 - Quentin Victor, Ianis Clavier, Hugo Boisaubert, Fabien Picarougne, Corinne Lejus-Bourdeau, Christine Sinoquet:
Two-in-One Models for Event Prediction and Time Series Forecasting. Comparison of Four Deep Learning Approaches to Simulate a Digital Patient Under Anesthesia. 373-388 - Miro Miranda, Francisco Alejandro Mena, Andreas Dengel:
An Analysis of Temporal Dropout in Earth Observation Time Series for Regression Tasks. 389-402 - Maciej Makowski, Brandon Gower-Winter, Georg Krempl:
Performative Drift Resistant Classification Using Generative Domain Adversarial Networks. 403-416
Explainable and Interpretable Data Science
- Rik Adriaensen, Jaron Maene:
Extracting Moore Machines from Transformers Using Queries and Counterexamples. 419-431 - Genghua Dong, Henrik Boström, Michalis Vazirgiannis, Roman Bresson:
Obtaining Example-Based Explanations from Deep Neural Networks. 432-443 - Dongwhi Kim, Nuno Moniz:
Relevance-Aware Algorithmic Recourse. 444-455 - Rikard Vinge, Stefan Byttner, Jens Lundström:
Expanding Polynomial Kernels for Global and Local Explanations of Support Vector Machines. 456-468 - Mathieu Guilbert, Christel Vrain, Thi-Bich-Hanh Dao:
A Constrained Declarative Based Approach for Explainable Clustering. 469-483
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