Machine Learning, Optimization, and Data Science 9th International Conference, LOD 2023, Grasmere, UK, September 22–26, 2023, Revised Selected Papers, Part I

Consensus-based Participatory Budgeting for Legitimacy: Decision Support via Multi-agent Reinforcement Learning.- Leverage Mathematics? capability to compress and generalize as application of ML Embedding extraction from LLMs and its adaptation in the Automotive Space.- Speeding up Logic-Based Benders Decomposition by Strengthening Cuts with Graph Neural Networks.- 38 Flocking Method for Identifying of Neural Circuits in Optogenetic Datasets.- A Machine Learning Approach for Source Code Similarity via Graph-focused Features.- Knowledge distillation with Segment Anything (SAM) model for Planetary Geological Mapping.- ContainerGym: A Real-World Reinforcement Learning Benchmark for Resource Allocation.- Perceptrons Under Veri able Random Data Corruption.- 104 Dynamic Soaring in Uncertain Wind Conditions: Polynomial Chaos Expansion Approach.- Solving Continuous Optimization Problems with a new Hyperheuristic Framework.-Benchmarking Named Entity Recognition Approaches for Extracting Research Infrastructure Information from Text.- Genetic Programming with Synthetic Data for Interpretable Regression Modelling and Limited Data.- A FastMap-Based Framework for E ciently Computing Top-K Projected Centrality.- Comparative analysis of machine learning models for time-series forecasting of Escherichia coli contamination in Portuguese shell sh production areas.- The Price of Data Processing Gail Gilboa Freedman.- Reward Shaping for Job Shop Scheduling.- A 3D Terrain Generator: Enhancing Robotics Simulations with GANs.- Hybrid Model for Impact Analysis of Climate Change on Droughts in Indian Region.- Bilevel Optimization by Conditional Bayesian Optimization.- Few-Shot Learning for Character Recognition in Persian Historical Documents.- ProVolOne ? Protein Volume Prediction Using a Multi-Attention, Multi-Resolution Deep Neural Network andFinite Element Analysis.- A data-driven monitoring approach for diagnosing quality degradation in a glass containerprocess.- Exploring emergent properties of recurrent neural networks using novel energy function formalism.- Co-Imagination of Behaviour & Morphology of Agents.- An Evolutionary Approach to Feature Selection and Classification.- "It Looks All the Same to Me": Cross-index Training for Long-term Financial Series Prediction.- U-FLEX: Unsupervised Feature Learning with Evolutionary eXploration.- Improved Filter-Based Feature Selection Techniques Based on Correlation and Clustering Techniques.- Deep Active Learning with Concept Drifts for detection of Mercury's Bow Shock and Magnetopause Crossings.- Modeling Primacy, Recency, and Cued recall in serial memory task using on-center o -surround recurrent neural network.- Joining Emission Data from Diverse Economical Activity Taxonomies with Evolution Strategies.- GRAN is superior to GraphRNN: node orderings, kernel- and graph embeddings-based metrics for graph generators.- Can Complexity Measures and Instance Hardness Measures Reflect the Actual Complexity of Microarray Data.- Two Steps Forward and One Behind: Rethinking Time Series Forecasting with Deep Learning.- Real-Time Emotion Recognition in Online Video Conferences for Medical Consultations.- Attentive perturbation: extending pre x tuning to large language models inner representations.- SoftCut: a fully di erentiable relaxed graph cut approach for deep learning image segmentation.