LEADER 05561nam 22005295 450 001 9910984687903321 005 20250304115225.0 010 $a9783031824814$b(electronic bk.) 010 $z9783031824807 024 7 $a10.1007/978-3-031-82481-4 035 $a(MiAaPQ)EBC31942160 035 $a(Au-PeEL)EBL31942160 035 $a(CKB)37772227300041 035 $a(DE-He213)978-3-031-82481-4 035 $a(OCoLC)1511101068 035 $a(EXLCZ)9937772227300041 100 $a20250304d2025 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aMachine Learning, Optimization, and Data Science $e10th International Conference, LOD 2024, Castiglione della Pescaia, Italy, September 22?25, 2024, Revised Selected Papers, Part I /$fedited by Giuseppe Nicosia, Varun Ojha, Sven Giesselbach, M. Panos Pardalos, Renato Umeton 205 $a1st ed. 2025. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2025. 215 $a1 online resource (826 pages) 225 1 $aLecture Notes in Computer Science,$x1611-3349 ;$v15508 311 08$aPrint version: Nicosia, Giuseppe Machine Learning, Optimization, and Data Science Cham : Springer,c2025 9783031824807 327 $a -- Solving Two-Stage Stochastic Programming problems via Machine Learning. -- Weight-varying Model Predictive Control for Coupled Cyber-Physical Systems: Aerial Grasping Study. -- Assessing the Impact of Government Policies on Covid-19 Spread: A Machine Learning Approach. -- Optimal Design and Implementation of an Open-source Emulation Platform for User-Centric Shared E-mobility Services. -- Protein Sequence Generation using Denoising Probabilistic Diffusion Model. -- Individual Fairness in Generative Text Models. -- Refined Direct Preference Optimization with Synthetic Data for Behavioral Alignment of LLMs. -- Artificial Intelligence and Cyber Security. -- Exploring Digital Health Trends in the Headlines via Knowledge Graph Analysis. -- Robust Infidelity: When Faithfulness Measures on Masked Language Models Are Misleading. -- Optimal risk scores for continuous predictors. -- Post-Treatment Gait Prediction after Botulinum Toxin Injections Using Deep Learning with an Attention Mechanism. -- Leveraging Graph Networks and Generative Adversarial Networks for Controllable Trajectory Prediction. -- Nearest Neighbors Counterfactuals. -- An Attention-based Representation Distillation Baseline for Multi-Label Continual Learning. -- Pattern detection in abnormal district heating data. -- Harnessing Graph Neural Networks for Pattern Classification in Heterogeneous Event Graphs. -- Learn to Create Neighborhoods in Real-World Vehicle Routing Problem. -- PointerKex: A Pointer-based SSH Key Extraction method. -- Addressing The Permutation Flowshop Scheduling with Grey Wolf Optimizer. -- MCGRAN: Multi-Conditional Graph Generation for Neural Architecture Search. -- Generative reward machine for Reinforcement learning for Physical Internet Distribution Centre. -- Between accurate prediction and poor decision making: the AI/ML gap. -- Cross-Metapath based Hashing for Recommendation Systems. -- Beyond Iterative Tuning: Zero-Shot Hyperparameter Optimisation for Decision Trees. -- Augmented Human-AI Forecasting for Ship Refit Project Scheduling: A Predict-then-Optimize Approach. -- Evaluation of Document Deduplication Algorithms for Large Text Corpora. -- Hicks Traverse meets One-Factor SVM: Belief Incoherence Attractors. -- Synthetic Time Series for Anomaly Detection in Cloud Microservices. -- Radiotherapy Treatment Planning: An Integrated Optimization and Reinforcement Learning Approach. -- Leap: Inductive Link Prediction via Learnable Topology Augmentation. -- Estimating Completeness of Consensus Models: Geometrical and Distributional Approaches. -- Active Inference Meeting Energy-Efficient Control of Parallel and Identical Machines. -- Clarifying the Fog: Evaluating and Enhancing User Comprehension of Android Data Safety Documents. 330 $aThe three-volume set LNAI 15508-15510 constitutes the refereed proceedings of the 10th International Conference on Machine Learning, Optimization, and Data Science, LOD 2024, held in Castiglione della Pescaia, Italy, during September 22?25, 2024. This year, in the LOD Proceedings decided to also include the papers of the fourth edition of the Symposium on Artificial Intelligence and Neuroscience (ACAIN 2024). The 79 full papers included in this book were carefully reviewed and selected from 127 submissions. The LOD 2024 proceedings focus on machine learning, deep learning, AI, computational optimization, neuroscience and big data that includes invited talks, tutorial talks, special sessions, industrial tracks, demonstrations and oral and poster presentations of refereed papers. 410 0$aLecture Notes in Computer Science,$x1611-3349 ;$v15508 606 $aArtificial intelligence 606 $aArtificial Intelligence 615 0$aArtificial intelligence. 615 14$aArtificial Intelligence. 676 $a006.3 700 $aNicosia$b Giuseppe$0241374 701 $aOjha$b Varun$01726448 701 $aGiesselbach$b Sven$01736135 701 $aPardalos$b M. Panos$01789844 701 $aUmeton$b Renato$01726451 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 912 $a9910984687903321 996 $aMachine Learning, Optimization, and Data Science$94325960 997 $aUNINA