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

Aus der Reihe Lecture Notes in Computer Science
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Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

15.02.2024

Herausgeber

Giuseppe Nicosia + weitere

Verlag

Springer

Seitenzahl

483

Maße (L/B/H)

23,5/15,5/2,8 cm

Gewicht

762 g

Auflage

1st edition 2024

Sprache

Englisch

ISBN

978-3-031-53965-7

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

15.02.2024

Herausgeber

Verlag

Springer

Seitenzahl

483

Maße (L/B/H)

23,5/15,5/2,8 cm

Gewicht

762 g

Auflage

1st edition 2024

Sprache

Englisch

ISBN

978-3-031-53965-7

Herstelleradresse

Springer-Verlag KG
Sachsenplatz 4-6
1201 Wien
AT

Email: GPSR Kontakt

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  • Produktbild: Machine Learning, Optimization, and Data Science
  • Produktbild: Machine Learning, Optimization, and Data Science
  • 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 spanning tree 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.