Machine Learning, Optimization, and Data Science

Table of Contents

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   Book Overview
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   Chapter 1 Integrated Human-AI Forecasting for Preventive Maintenance Task Duration Estimation
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   Chapter 2 Exploring Image Transformations with Diffusion Models: A Survey of Applications and Implementation Code
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   Chapter 3 Geolocation Risk Scores for Credit Scoring Models
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   Chapter 4 Social Media Analysis: The Relationship Between Private Investors and Stock Price
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   Chapter 5 Deep Learning Model of Two-Phase Fluid Transport Through Fractured Media: A Real-World Case Study
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   Chapter 6 A Proximal Algorithm for Network Slimming
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   Chapter 7 Diversity in Deep Generative Models and Generative AI
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   Chapter 8 Improving Portfolio Performance Using a Novel Method for Predicting Financial Regimes
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    Chapter 9 Ökolopoly: Case Study on Large Action Spaces in Reinforcement Learning
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    Chapter 10 Alternating Mixed-Integer Programming and Neural Network Training for Approximating Stochastic Two-Stage Problems
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    Chapter 11 Heaviest and Densest Subgraph Computation for Binary Classification. A Case Study
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    Chapter 12 SMBOX: A Scalable and Efficient Method for Sequential Model-Based Parameter Optimization
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    Chapter 13 Accelerated Graph Integration with Approximation of Combining Parameters
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    Chapter 14 Improving Reinforcement Learning Efficiency with Auxiliary Tasks in Non-visual Environments: A Comparison
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    Chapter 15 A Hybrid Steady-State Genetic Algorithm for the Minimum Conflict Spanning Tree Problem
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    Chapter 16 Reinforcement Learning for Multi-Neighborhood Local Search in Combinatorial Optimization
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    Chapter 17 Evaluation of Selected Autoencoders in the Context of End-User Experience Management
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    Chapter 18 Application of Multi-agent Reinforcement Learning to the Dynamic Scheduling Problem in Manufacturing Systems
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    Chapter 19 Solving Mixed Influence Diagrams by Reinforcement Learning
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    Chapter 20 Multi-scale Heat Kernel Graph Network for Graph Classification
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    Chapter 21 PROS-C: Accelerating Random Orthogonal Search for Global Optimization Using Crossover
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    Chapter 22 A Multiclass Robust Twin Parametric Margin Support Vector Machine with an Application to Vehicles Emissions
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    Chapter 23 LSTM Noise Robustness: A Case Study for Heavy Vehicles
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    Chapter 24 Ensemble Clustering for Boundary Detection in High-Dimensional Data
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    Chapter 25 Learning Graph Configuration Spaces with Graph Embedding in Engineering Domains
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    Chapter 26 Towards an Interpretable Functional Image-Based Classifier: Dimensionality Reduction of High-Density Diffuse Optical Tomography Data
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    Chapter 27 On Ensemble Learning for Mental Workload Classification
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    Chapter 28 Decision-Making over Compact Preference Structures
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    Chapter 29 User-Like Bots for Cognitive Automation: A Survey
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    Chapter 30 On Channel Selection for EEG-Based Mental Workload Classification
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    Chapter 31 What Song Am I Thinking Of?
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    Chapter 32 Path-Weights and Layer-Wise Relevance Propagation for Explainability of ANNs with fMRI Data
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    Chapter 33 Sensitivity Analysis for Feature Importance in Predicting Alzheimer’s Disease
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    Chapter 34 A Radically New Theory of How the Brain Represents and Computes with Probabilities