Abstract is missing.
- Credal Knowledge Tracing for Imprecise and Uncertain MCQDorra Sassi, Constance Thierry, David Gross-Amblard. 3-16 [doi]
- Development of Models to Quantify Training Load in Outdoor Running Using Inertial SensorsBouke L. Scheltinga, Jasper Reenalda, Jaap H. Buurke, Joost N. Kok. 17-27 [doi]
- Estimating the Learning Capacity of Bacterial Metabolic NetworksBastien Mollet, Paul Ahavi, Antoine Cornuéjols, Jean-Loup Faulon, Evelyne Lutton, Alberto Tonda. 28-40 [doi]
- Semi-supervised Learning with Pairwise Instance Comparisons for Medical Instance ClassificationAnne Rother, Till Ittermann, Myra Spiliopoulou. 41-53 [doi]
- Local-Global Data Augmentation for Contrastive Learning in Static Sign Language RecognitionAriel Basso Madjoukeng, Kenmogne Edith Belise, Pierre Poitier, Benoît Frénay, Jérôme Fink. 54-66 [doi]
- SiamCircle: Trajectory Representation Learning in Free SettingsMaedeh Nasri, Mitra Baratchi, Alexander Koutamanis, Carolien Rieffe. 67-80 [doi]
- Synthetic Tabular Data Detection in the WildG. Charbel N. Kindji, Elisa Fromont, Lina Maria Rojas-Barahona, Tanguy Urvoy. 81-96 [doi]
- Assessing the Graph Structure Learning in Graph Deviation NetworksCanberk Ozen, Slawomir Nowaczyk, Prayag Tiwari, Sepideh Pashami. 97-109 [doi]
- The When and How of Target Variable TransformationsLoren Nuyts, Jesse Davis. 113-126 [doi]
- Balancing Performance and Scalability of Demand Forecasting ML ModelsMateusz Zarski, Slawomir Nowaczyk. 127-140 [doi]
- Balancing Global Importance and Source Proximity for Personalized Recommendations Using Random Walk LengthTsuyoshi Yamashita, Kunitake Kaneko. 141-153 [doi]
- Counterintuitive Behavior of Clustering Quality: Findings for K-Means on Synthetic and Real DataMarco Loog, Jesse H. Krijthe, Manuele Bicego. 154-166 [doi]
- BOWSA: A Contribution of Sensitivity Analysis to Improve Bayesian Optimization for Parameter TuningLise Kastner, Bertrand Cuissart, Jean Luc Lamotte. 167-180 [doi]
- Overfitting in Combined Algorithm Selection and Hyperparameter OptimizationSietse Schröder, Mitra Baratchi, Jan N. van Rijn. 181-194 [doi]
- Local Subgroup Discovery on Attributed Network GraphsCarl Vico Heinrich, Tommie Lombarts, Jules Mallens, Luc Tortike, David Wolf, Wouter Duivesteijn. 195-208 [doi]
- Imposing Constraints in Probabilistic Circuits via Gradient OptimizationSoroush Ghandi, Benjamin Quost, Cassio de Campos. 209-220 [doi]
- Improving Next Tokens via Second-to-Last Predictions with Generate and RefineJohannes Schneider. 223-233 [doi]
- Detection of Large Language Model Contamination with Tabular DataBenoît Ronval, Pierre Dupont, Siegfried Nijssen. 234-245 [doi]
- Imbalanced Data Clustering via Targeted Data Augmentation Using GMM and LLMNoor Khalal, Abdallah Alaa-Eddine Djamai, Imed Keraghel, Mohamed Nadif. 246-260 [doi]
- Make Literature-Based Discovery Great Again Through Reproducible PipelinesBojan Cestnik, Andrej Kastrin, Boshko Koloski, Nada Lavrac. 261-273 [doi]
- Extracting Information in a Low-Resource Setting: Case Study on Bioinformatics WorkflowsClémence Sebe, Sarah Cohen Boulakia, Olivier Ferret, Aurélie Névéol. 274-287 [doi]
- Vocabulary Quality in NLP Datasets: An Autoencoder-Based Framework Across Domains and LanguagesVu Minh Hoang Dang, Rakesh M. Verma. 288-301 [doi]
- Expertise Prediction of Tetris Players Using Eye Tracking InformationStijn J. Rotman, Gianluca Guglielmo, Boris Cule, Michal Klincewicz. 305-317 [doi]
- Integrating Inverse and Forward Modeling for Sparse Temporal Data from Sensor NetworksJulian Vexler, Björn Vieten, Martin Nelke, Stefan Kramer 0001. 318-329 [doi]
- Bridging Spatial and Temporal Contexts: Sparse Transfer LearningDaniel Persson, William Wahlberg, Anna Vettoruzzo, Slawomir Nowaczyk. 330-342 [doi]
- Meta-learning and Data Augmentation for Stress Testing Forecasting ModelsRicardo Inácio, Vítor Cerqueira, Marília Barandas, Carlos Soares. 343-357 [doi]
- Pragmatic Paradigm for Multi-stream RegressionNuwan Gunasekara, Slawomir Nowaczyk, Sepideh Pashami. 358-372 [doi]
- Two-in-One Models for Event Prediction and Time Series Forecasting. Comparison of Four Deep Learning Approaches to Simulate a Digital Patient Under AnesthesiaQuentin Victor, Ianis Clavier, Hugo Boisaubert, Fabien Picarougne, Corinne Lejus-Bourdeau, Christine Sinoquet. 373-388 [doi]
- An Analysis of Temporal Dropout in Earth Observation Time Series for Regression TasksMiro Miranda, Francisco Alejandro Mena, Andreas Dengel 0001. 389-402 [doi]
- Performative Drift Resistant Classification Using Generative Domain Adversarial NetworksMaciej Makowski, Brandon Gower-Winter, Georg Krempl. 403-416 [doi]
- Extracting Moore Machines from Transformers Using Queries and CounterexamplesRik Adriaensen, Jaron Maene. 419-431 [doi]
- Obtaining Example-Based Explanations from Deep Neural NetworksGenghua Dong, Henrik Boström, Michalis Vazirgiannis, Roman Bresson. 432-443 [doi]
- Relevance-Aware Algorithmic RecourseDongwhi Kim, Nuno Moniz. 444-455 [doi]
- Expanding Polynomial Kernels for Global and Local Explanations of Support Vector MachinesRikard Vinge, Stefan Byttner, Jens Lundström. 456-468 [doi]
- A Constrained Declarative Based Approach for Explainable ClusteringMathieu Guilbert, Christel Vrain, Thi-Bich-Hanh Dao. 469-483 [doi]