Machine Learning, Optimization, and Data Science

Machine Learning, Optimization, and Data Science portes grátis

Machine Learning, Optimization, and Data Science

9th International Conference, LOD 2023, Grasmere, UK, September 22-26, 2023, Revised Selected Papers, Part II

La Malfa, Gabriele; Nicosia, Giuseppe; Umeton, Renato; Pardalos, Panos M.; La Malfa, Emanuele; Ojha, Varun

Springer International Publishing AG

02/2024

483

Mole

Inglês

9783031539657

15 a 20 dias

Descrição não disponível.
Integrated Human-AI Forecasting for Preventive Maintenance Task Duration Estimation.- Exploring Image Transformations with Diffusion Models: A Survey of Applications and Implementation Code.- Geolocation Risk Scores for Credit Scoring Models.- Social Media Analysis: The Relationship between Private Investors and Stock Price.- Deep learning model of two-phase fluid transport through fractured media: a real-world case study.- A Proximal Algorithm for Network Slimming.- Diversity in deep generative models and generative AI.- Improving Portfolio Performance Using a Novel Method for Predicting Financial Regimes.- kolopoly: Case Study on Large Action Spaces in Reinforcement Learning.- Alternating mixed-integer programming and neural network training for approximating stochastic two-stage problems.- Heaviest and densest subgraph computation for binary classification. A case study.- SMBOX: A Scalable and Efficient Method for Sequential Model-Based Parameter Optimization.- Accelerated Graph Integration with Approximation of Combining Parameters.- Improving Reinforcement Learning Efficiency with Auxiliary Tasks in Non-Visual Environments: A Comparison.- A hybrid steady-state genetic algorithm for the minimum conflict spanningtree problem.- Reinforcement learning for multi-neighborhood local search in combinatorial optimization.- Evaluation of Selected Autoencoders in the Context of End-User Experience Management.- Application of multi-agent reinforcement learning to the dynamic scheduling problem in manufacturing systems.- Solving Mixed Influence Diagrams by Reinforcement Learning.- Multi-Scale Heat Kernel Graph Network for Graph Classification.- Accelerating Random Orthogonal Search for Global Optimization using Crossover.- A Multiclass Robust Twin Parametric Margin Support Vector Machine with an Application toVehicles Emissions.- LSTM noise robustness: a case study for heavy vehicles.- Ensemble Clustering for Boundary Detection in High-Dimensional Data.- Learning Graph Configuration Spaces with Graph Embedding in Engineering Domains.- Towards an Interpretable Functional Image-Based Classifier: Dimensionality.- Reduction of High-Density Di use Optical Tomography Data.- On Ensemble Learning for Mental Workload Classification.- Decision-making over compact preference structures.- User-Like Bots for Cognitive Automation: A Survey.- On Channel Selection for EEG-based Mental Workload Classification.- What Song Am I Thinking Of.- Path-Weights and Layer-Wise Relevance Propagation for Explainability of ANNs with fMRI Data.- Sensitivity Analysis for Feature Importance in Predicting Alzheimer?s Disease.- A Radically New Theory of how the Brain Represents and Computes with Probabilities.
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computer security;evolutionary algorithms;fuzzy control;image processing;database systems;artificial intelligence;Bayesian networks;big data;deep learning;machine learning