東華大學圖書館 |

Machine learning, optimization, and data science = 9th International Workshop, LOD 2023, Grasmere, UK, September 22-26, 2023 : revised selected papers.. Part II /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Machine learning, optimization, and data science/ edited by Giuseppe Nicosia ... [et al.].
Reminder of title:	9th International Workshop, LOD 2023, Grasmere, UK, September 22-26, 2023 : revised selected papers.
remainder title:	LOD 2023
other author:	Nicosia, Giuseppe.
corporate name:	LOD (Conference)
Published:	Cham :Springer Nature Switzerland : : 2024.,
Description:	xxii, 483 p. :ill. (chiefly col.), digital ;24 cm.
[NT 15003449]:	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 to Vehicles 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.
Contained By:	Springer Nature eBook
Subject:	Machine learning - Congresses. -
Online resource:	https://doi.org/10.1007/978-3-031-53966-4
ISBN:	9783031539664

Machine learning, optimization, and data science = 9th International Workshop, LOD 2023, Grasmere, UK, September 22-26, 2023 : revised selected papers.. Part II /
Machine learning, optimization, and data science9th International Workshop, LOD 2023, Grasmere, UK, September 22-26, 2023 : revised selected papers.Part II /[electronic resource] :LOD 2023edited by Giuseppe Nicosia ... [et al.]. - Cham :Springer Nature Switzerland :2024. - xxii, 483 p. :ill. (chiefly col.), digital ;24 cm. - Lecture notes in computer science,145060302-9743 ;. - Lecture notes in computer science ;14506..

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 to Vehicles 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.

This book constitutes the refereed proceedings of the 9th International Conference on Machine Learning, Optimization, and Data Science, LOD 2023, which took place in Grasmere, UK, in September 2023. The 72 full papers included in this book were carefully reviewed and selected from 119 submissions. The proceedings also contain 9 papers from and the Third Symposium on Artificial Intelligence and Neuroscience, ACAIN 2023. The contributions focus on the state of the art and the latest advances in the integration of machine learning, deep learning, nonlinear optimization and data science to provide and support the scientific and technological foundations for interpretable, explainable and trustworthy AI.

ISBN: 9783031539664

Standard No.: 10.1007/978-3-031-53966-4doiSubjects--Topical Terms:

576368
Machine learning
--Congresses.

LC Class. No.: Q325.5

Dewey Class. No.: 006.31

Machine learning, optimization, and data science = 9th International Workshop, LOD 2023, Grasmere, UK, September 22-26, 2023 : revised selected papers.. Part II /
LDR:04661nmm a2200349 a 4500 001 2368679
003 DE-He213
005 20240214180843.0
006 m d
007 cr nn 008maaau
008 241127s2024 sz s 0 eng d
020 $a 9783031539664 $q (electronic bk.)
020 $a 9783031539657 $q (paper)
024 7 $a 10.1007/978-3-031-53966-4 $2 doi
035 $a 978-3-031-53966-4
040 $a GP $c GP
041 0 $a eng
050 4 $a Q325.5
072 7 $a UF $2 bicssc
072 7 $a COM018000 $2 bisacsh
072 7 $a UXJ $2 thema
082 0 4 $a 006.31 $2 23
090 $a Q325.5 $b .L821 2023
111 2 $a LOD (Conference) $n (9th : $d 2023 : $c Grasmere, UK) $3 3712766
245 1 0 $a Machine learning, optimization, and data science $h [electronic resource] : $b 9th International Workshop, LOD 2023, Grasmere, UK, September 22-26, 2023 : revised selected papers. $n Part II / $c edited by Giuseppe Nicosia ... [et al.].
246 3 $a LOD 2023
260 $a Cham : $b Springer Nature Switzerland : $b Imprint: Springer, $c 2024.
300 $a xxii, 483 p. : $b ill. (chiefly col.), digital ; $c 24 cm.
490 1 $a Lecture notes in computer science, $x 0302-9743 ; $v 14506
505 0 $a 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 to Vehicles 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.
520 $a This book constitutes the refereed proceedings of the 9th International Conference on Machine Learning, Optimization, and Data Science, LOD 2023, which took place in Grasmere, UK, in September 2023. The 72 full papers included in this book were carefully reviewed and selected from 119 submissions. The proceedings also contain 9 papers from and the Third Symposium on Artificial Intelligence and Neuroscience, ACAIN 2023. The contributions focus on the state of the art and the latest advances in the integration of machine learning, deep learning, nonlinear optimization and data science to provide and support the scientific and technological foundations for interpretable, explainable and trustworthy AI.
650 0 $a Machine learning $x Congresses. $3 576368
650 0 $a Mathematical optimization $x Congresses. $3 647613
650 1 4 $a Computer Application in Administrative Data Processing. $3 3594379
650 2 4 $a Computer Communication Networks. $3 775497
650 2 4 $a System Performance and Evaluation. $3 891353
650 2 4 $a Computer System Implementation. $3 892710
650 2 4 $a Artificial Intelligence. $3 769149
650 2 4 $a Machine Learning. $3 3382522
700 1 $a Nicosia, Giuseppe. $3 1004633
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
830 0 $a Lecture notes in computer science ; $v 14506. $3 3712767
856 4 0 $u https://doi.org/10.1007/978-3-031-53966-4
950 $a Computer Science (SpringerNature-11645)