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Discovery Science

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Cover of 'Discovery Science'

Table of Contents

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    Book Overview
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    Chapter 1 Evaluating Decision Makers over Selectively Labelled Data: A Causal Modelling Approach
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    Chapter 2 Mitigating Discrimination in Clinical Machine Learning Decision Support Using Algorithmic Processing Techniques
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    Chapter 3 WeakAL : Combining Active Learning and Weak Supervision
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    Chapter 4 Constrained Clustering via Post-processing
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    Chapter 5 Deep Convolutional Embedding for Painting Clustering: Case Study on Picasso’s Artworks
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    Chapter 6 Dynamic Incremental Semi-supervised Fuzzy Clustering for Bipolar Disorder Episode Prediction
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    Chapter 7 Iterative Multi-mode Discretization: Applications to Co-clustering
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    Chapter 8 COVID-19 Therapy Target Discovery with Context-Aware Literature Mining
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    Chapter 9 Semantic Annotation of Predictive Modelling Experiments
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    Chapter 10 Semantic Description of Data Mining Datasets: An Ontology-Based Annotation Schema
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    Chapter 11 $$\mathsf {FABBOO}$$ - Online Fairness-Aware Learning Under Class Imbalance
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    Chapter 12 FEAT: A Fairness-Enhancing and Concept-Adapting Decision Tree Classifier
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    Chapter 13 Unsupervised Concept Drift Detection Using a Student–Teacher Approach
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    Chapter 14 Assembled Feature Selection for Credit Scoring in Microfinance with Non-traditional Features
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    Chapter 15 Learning Surrogates of a Radiative Transfer Model for the Sentinel 5P Satellite
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    Chapter 16 Nets Versus Trees for Feature Ranking and Gene Network Inference
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    Chapter 17 Pathway Activity Score Learning for Dimensionality Reduction of Gene Expression Data
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    Chapter 18 Balancing Between Scalability and Accuracy in Time-Series Classification for Stream and Batch Settings
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    Chapter 19 DeCStor: A Framework for Privately and Securely Sharing Files Using a Public Blockchain
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    Chapter 20 Investigating Parallelization of MAML
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    Chapter 21 Extreme Algorithm Selection with Dyadic Feature Representation
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    Chapter 22 Federated Ensemble Regression Using Classification
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    Chapter 23 One-Class Ensembles for Rare Genomic Sequences Identification
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    Chapter 24 Explaining Sentiment Classification with Synthetic Exemplars and Counter-Exemplars
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    Chapter 25 Generating Explainable and Effective Data Descriptors Using Relational Learning: Application to Cancer Biology
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    Chapter 26 Interpretable Machine Learning with Bitonic Generalized Additive Models and Automatic Feature Construction
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    Chapter 27 Predicting and Explaining Privacy Risk Exposure in Mobility Data
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    Chapter 28 Maximizing Network Coverage Under the Presence of Time Constraint by Injecting Most Effective k-Links
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    Chapter 29 On the Utilization of Structural and Textual Information of a Scientific Knowledge Graph to Discover Future Research Collaborations: A Link Prediction Perspective
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    Chapter 30 Simultaneous Process Drift Detection and Characterization with Pattern-Based Change Detectors
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    Chapter 31 Extreme Gradient Boosted Multi-label Trees for Dynamic Classifier Chains
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    Chapter 32 Hierarchy Decomposition Pipeline: A Toolbox for Comparison of Model Induction Algorithms on Hierarchical Multi-label Classification Problems
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    Chapter 33 Missing Value Imputation with MERCS: A Faster Alternative to MissForest
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    Chapter 34 Multi-directional Rule Set Learning
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    Chapter 35 On Aggregation in Ensembles of Multilabel Classifiers
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    Chapter 36 Attention in Recurrent Neural Networks for Energy Disaggregation
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    Chapter 37 Enhanced Food Safety Through Deep Learning for Food Recalls Prediction
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    Chapter 38 FairNN  - Conjoint Learning of Fair Representations for Fair Decisions
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    Chapter 39 Improving Deep Unsupervised Anomaly Detection by Exploiting VAE Latent Space Distribution
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    Chapter 40 Detecting Temporal Anomalies in Business Processes Using Distance-Based Methods
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    Chapter 41 Mining Constrained Regions of Interest: An Optimization Approach
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    Chapter 42 Mining Disjoint Sequential Pattern Pairs from Tourist Trajectory Data
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    Chapter 43 Predicting the Health Condition of mHealth App Users with Large Differences in the Number of Recorded Observations - Where to Learn from?
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    Chapter 44 Spatiotemporal Traffic Anomaly Detection on Urban Road Network Using Tensor Decomposition Method
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    Chapter 45 Time Series Regression in Professional Road Cycling
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