Advances in Intelligent Data Analysis XXIII: 23rd International Symposium on Intelligent Data Analysis, IDA 2025, Konstanz, Germany, May 79, 2025, Proceedings [Pehme köide]

Applications of Data Science.- Credal Knowledge Tracing for Imprecise
and Uncertain MCQ.- Development of Models to Quantify Training Load in
Outdoor Running using Inertial Sensors.- Estimating the Learning Capacity of
Bacterial Metabolic Networks.- Semi-supervised learning with pairwise
instance comparisons for medical instance classification.- Local-global Data
Augmentation for Contrastive Learning in Static Sign Language Recognition.-
SiamCircle: Trajectory Representation Learning in Free Settings.- Synthetic
Tabular Data Detection In the Wild.- Assessing the Impact of Graph Structure
Learning in Graph Deviation Networks.- Foundations of Data Science.- The When
and How of Target Variable Transformations.- Balancing performance and
scalability of demand forecasting ML models.- Balancing global importance and
source proximity for personalized recommendations using random walk length.-
Counterintuitive Behavior of Clustering Quality: Findings for K-Means
on Synthetic and Real Data.- BOWSA: a contribution of sensitivity analysis to
improve Bayesian optimization for parameter tuning.- Overfitting in Combined
Algorithm Selection and Hyperparameter
Optimization.- Local Subgroup Discovery on Attributed Network Graphs.-
Imposing Constraints in Probabilistic Circuits via Gradient Optimization.-
Natural Language Processing.- Improving Next Tokens via Second-Last
Predictions with Generate and Refine.- Detection of Large Language Model
Contamination with Tabular Data.- Imbalanced Data Clustering via Targeted
Data Augmentation Using GMM and LLM.- Make Literature-Based Discovery Great
Again through Reproducible Pipelines.- Extracting information in a
low-resource setting: case study on bioinformatics workflows.- Vocabulary
Quality in NLP Datasets: An Autoencoder-Based Framework Across Domains and
Languages.- Temporal and Streaming Data Expertise Prediction of Tetris
Players Using Eye Tracking Information.- Integrating Inverse and Forward
Modeling for Sparse Temporal Data from Sensor Networks.- Bridging Spatial and
Temporal Contexts: Sparse Transfer Learning.- Meta-learning and Data
Augmentation for Stress Testing Forecasting Models.- Pragmatic Paradigm for
Multi-stream Regression.- Two-in-one Models for Event Prediction and Time
Series Forecasting. Comparison of Four Deep Learning Approaches to Simulate a
Digital Patient under Anesthesia.- An Analysis of Temporal Dropout in Earth
Observation Time Series for Regression Tasks.- Performative Drift Resistant
Classification using Generative Domain Adversarial Networks.- Explainable and
Interpretable Data Science.- Extracting Moore Machines from Transformers
using Queries and Counterexamples.- Obtaining Example-Based Explanations from
Deep Neural Networks.- Relevance-aware Algorithmic Recourse.- Expanding
Polynomial Kernels for Global and Local Explanations of Support Vector
Machines.- A Constrained Declarative Based Approach for Explainable
Clustering.