Machine Learning, Optimization, and Data Science

Table of Contents

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   Book Overview
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   Chapter 1 Pooling Graph Convolutional Networks for Structural Performance Prediction
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   Chapter 2 A Game Theoretic Flavoured Decision Tree for Classification
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   Chapter 3 Human-Centric Machine Learning Approach for Injection Mold Design: Towards Automated Ejector Pin Placement
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   Chapter 4 A Generative Adversarial Network Based Approach to Malware Generation Based on Behavioural Graphs
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   Chapter 5 Multi-omic Data Integration and Feature Selection for Survival-Based Patient Stratification via Supervised Concrete Autoencoders
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   Chapter 6 Smart Pruning of Deep Neural Networks Using Curve Fitting and Evolution of Weights
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   Chapter 7 Biologically Inspired Unified Artificial Immune System for Industrial Equipment Diagnostic
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   Chapter 8 A Nonparametric Pooling Operator Capable of Texture Extraction
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    Chapter 9 Strategic Workforce Planning with Deep Reinforcement Learning
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    Chapter 10 Enhanced Association Rules and Python
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    Chapter 11 Generating Vascular Networks: A Reinforcement Learning Approach
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    Chapter 12 Expressive and Intuitive Models for Automated Context Representation Learning in Credit-Card Fraud Detection
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    Chapter 13 Digital Twins: Modelling Languages Comparison
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    Chapter 14 Algorithms that Get Old: The Case of Generative Deep Neural Networks
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    Chapter 15 A Two-Country Study of Default Risk Prediction Using Bayesian Machine-Learning
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    Chapter 16 Enforcing Hard State-Dependent Action Bounds on Deep Reinforcement Learning Policies
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    Chapter 17 A Bee Colony Optimization Approach for the Electric Vehicle Routing Problem with Drones
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    Chapter 18 Best Practices in Flux Sampling of Constrained-Based Models
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    Chapter 19 EFI: A Toolbox for Feature Importance Fusion and Interpretation in Python
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    Chapter 20 Hierarchical Decentralized Deep Reinforcement Learning Architecture for a Simulated Four-Legged Agent
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    Chapter 21 Robust PCA for Anomaly Detection and Data Imputation in Seasonal Time Series
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    Chapter 22 Monte Carlo Optimization of Liver Machine Perfusion Temperature Policies
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    Chapter 23 A Comparison of SVM Against Pre-trained Language Models (PLMs) for Text Classification Tasks
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    Chapter 24 Normalization in Motif Discovery
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    Chapter 25 Tree-Based Credit Card Fraud Detection Using Isolation Forest, Spectral Residual, and Knowledge Graph
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    Chapter 26 A Variational Algorithm for Quantum Single Layer Perceptron
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    Chapter 27 Preconditioned Gradient Method for Data Approximation with Shallow Neural Networks
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    Chapter 28 Grid-Based Contraction Clustering in a Peer-to-Peer Network
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    Chapter 29 Surrogate Modeling for Stochastic Assessment of Engineering Structures
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    Chapter 30 On Time Series Cross-Validation for Deep Learning Classification Model of Mental Workload Levels Based on EEG Signals
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    Chapter 31 Path Weights Analyses in a Shallow Neural Network to Reach Explainable Artificial Intelligence (XAI) of fMRI Data
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    Chapter 32 Audio Visual Association Test in Non Synesthetic Subjects: Technological Tailoring of the Methods
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    Chapter 33 Flow Control: Local Spectral Radius Regulation
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    Chapter 34 Neural Correlates of Satisfaction of an Information Need
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    Chapter 35 Role of Punctuation in Semantic Mapping Between Brain and Transformer Models
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    Chapter 36 A Bayesian-Optimized Convolutional Neural Network to Decode Reach-to-Grasp from Macaque Dorsomedial Visual Stream
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    Chapter 37 Brain-like Combination of Feedforward and Recurrent Network Components Achieves Prototype Extraction and Robust Pattern Recognition
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    Chapter 38 Thinking Fast and Slow in AI: The Role of Metacognition
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    Chapter 39 Confidence as Part of Searcher’s Cognitive Context
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    Chapter 40 Brain Structural Saliency over the Ages
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    Chapter 41 Revisiting Neurological Aspects of Relevance: An EEG Study
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    Chapter 42 BioLCNet: Reward-Modulated Locally Connected Spiking Neural Networks