Discovery Science

Table of Contents

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   Book Overview
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   Chapter 1 Context-Based Abrupt Change Detection and Adaptation for Categorical Data Streams
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   Chapter 2 A New Adaptive Learning Algorithm and Its Application to Online Malware Detection
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   Chapter 3 Real-Time Validation of Retail Gasoline Prices
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   Chapter 4 General Meta-Model Framework for Surrogate-Based Numerical Optimization
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   Chapter 5 Evaluation of Different Heuristics for Accommodating Asymmetric Loss Functions in Regression
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   Chapter 6 Differentially Private Empirical Risk Minimization with Input Perturbation
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   Chapter 7 On a New Competence Measure Applied to the Dynamic Selection of Classifiers Ensemble
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   Chapter 8 Multi-label Classification Using Random Label Subset Selections
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    Chapter 9 Option Predictive Clustering Trees for Hierarchical Multi-label Classification
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    Chapter 10 Re-training Deep Neural Networks to Facilitate Boolean Concept Extraction
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    Chapter 11 An In-Depth Experimental Comparison of RNTNs and CNNs for Sentence Modeling
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    Chapter 12 Improving Classification Accuracy by Means of the Sliding Window Method in Consistency-Based Feature Selection
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    Chapter 13 Feature Ranking for Multi-target Regression with Tree Ensemble Methods
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    Chapter 14 Recommending Collaborative Filtering Algorithms Using Subsampling Landmarkers
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    Chapter 15 Recursive Extraction of Modular Structure from Layered Neural Networks Using Variational Bayes Method
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    Chapter 16 Discovering Hidden Knowledge in Carbon Emissions Data: A Multilayer Network Approach
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    Chapter 17 Topic Extraction on Twitter Considering Author’s Role Based on Bipartite Networks
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    Chapter 18 Mining Strongly Closed Itemsets from Data Streams
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    Chapter 19 Extracting Mutually Dependent Multisets
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    Chapter 20 LOCANDA: Exploiting Causality in the Reconstruction of Gene Regulatory Networks
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    Chapter 21 Discovery of Salivary Gland Tumors’ Biomarkers via Co-Regularized Sparse-Group Lasso
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    Chapter 22 Measuring the Inspiration Rate of Topics in Bibliographic Networks
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    Chapter 23 Discovering Minority Sub-clusters and Local Difficulty Factors from Imbalanced Data
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    Chapter 24 Fusion Techniques for Named Entity Recognition and Word Sense Induction and Disambiguation