Main Track: Optimization of Image Acquisition for Earth Observation Satellites via Quantum Computing -- Complexity-driven sampling for Bagging -- A pseudo-label guided hybrid approach for unsupervised domain adaptation⋆ -- Combining of Markov Random Field and Convolutional Neural Networks for Hyper/Multispectral Image Classification -- Plant Disease Detection and Classification using a Deep learning-based framework -- Evaluating Text Classification in the Legal Domain Using BERT Embeddings -- Rapid and Low-Cost Evaluation of Multi-Fidelity Scheduling Algorithms for Hyperparameter Optimization -- The Applicability of Federated Learning to Official Statistics -- Generating Wildfire Heat Maps with Twitter and BERT -- An urban simulator integrated with a genetic algorithm for efficient traffic light coordination -- GPU-Based Acceleration of the Rao Optimization Algorithms: Application to the Solution of Large Systems of Nonlinear Equations -- Direct determination of Operational Value-at-Risk using Descriptive Statistics -- Using Deep Learning models to Predict the Electrical Conductivity of the influent in a Wastewater Treatment Plant. -Unsupervised Defect Detection for Infrastructure Inspection -- Generating Adversarial Examples using LAD -- Emotion extraction from Likert-Scale questionnaires - an additional dimension to Psychology Instruments -- Recent applications of pre-aggregation functions -- A Probabilistic Approach: Querying Web Resources In The Presence Of Uncertainty -- Domain Adaptation in Transformer models: Question Answering of Dutch Government Policies -- Sustainable On-Street Parking Mapping with Deep Learning and Airborne Imagery -- Hebbian Learning-Guided Random Walks for Enhanced Community Detection in Correlation-Based Brain Networks -- Hebbian Learning-Guided Random Walks for Enhanced Community Detection in Correlation-Based Brain Networks -- Language Models for Automatic Distribution of Review Notes in Movie Production -- Extracting Knowledge from Incompletely Known Models -- Threshold-based Classification to Enhance Confidence in Open Set of Legal Texts -- Comparing ranking learning algorithms for information retrieval systems -- Analyzing the influence of market event correction for forecasting stock prices using Recurrent Neural Networks -- Measuring the relationship between the use of typical Manosphere discourse and the engagement of a user with the pick-up artist community⋆ -- Uniform Design of Experiments for Equality Constraints -- Globular Cluster Detection in M33 Using Multiple Views Representation Learning -- Segmentation of Brachial Plexus Ultrasound Images Based on Modified SegNet Model -- Unsupervised Online Event Ranking for IT Operations⋆ -- A Subgraph Embedded GIN with Attention for Graph Classification -- A Machine Learning Approach to Predict Cyclists' Functional Threshold Power -- Combining Regular Expressions and Supervised Algorithms for Clinical Text Classification -- MODELING THE INK TUNING PROCESS USING MACHINE LEARNING -- Depth and Width Adaption of DNN for Data Stream Classification with Concept Drifts* -- FETCH: A Memory-Efficient Replay Approach for Continual Learning in Image Classification -- Enhanced SVM-SMOTE with Cluster Consistency for Imbalanced Data Classification -- Preliminary Study on Unexploded Ordnance Classification in Underwater Environment Based on the Raw Magnetometry Data. -- Efficient Model For Probabilistic Web resources under uncertainty -- Unlocking the Black Box: Towards Interactive Explainable Automated Machine Learning -- Machine Learning for Time Series Forecasting Using State Space Models -- Causal graph discovery for explainable insights on marine biotoxin shellfish contamination -- Special Session on Federated Learning and (pre) Aggregation in Machine Learning: Adaptative fuzzy measure for edge detection -- Special Session on Intelligent Techniques for Real-world Applications of Renewable Energy and Green Transport: Prediction and Uncertainty Estimation in Power Curves of Wind Turbines Using ε-SVR -- Glide Ratio Optimization for Wind Turbine Airfoils based on Genetic Algorithms -- Special Session on Data Selection in Machine Learning: Detecting Image Forgery Using Support Vector Machine and Texture Features -- Instance selection techniques for large volumes of data.