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Machine Learning and Knowledge Extraction

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Cover of 'Machine Learning and Knowledge Extraction'

Table of Contents

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    Book Overview
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    Chapter 2 Machine Learning Explainability Through Comprehensible Decision Trees
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    Chapter 7 Physiological Indicators for User Trust in Machine Learning with Influence Enhanced Fact-Checking
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    Chapter 12 Machine Learning for Family Doctors: A Case of Cluster Analysis for Studying Aging Associated Comorbidities and Frailty
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    Chapter 13 Knowledge Extraction for Cryptographic Algorithm Validation Test Vectors by Means of Combinatorial Coverage Measurement
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    Chapter 14 An Evaluation on Robustness and Utility of Fingerprinting Schemes
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    Chapter 15 Differentially Private Obfuscation of Facial Images
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    Chapter 19 Deep Learning for Proteomics Data for Feature Selection and Classification
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    Chapter 22 A Case for Guided Machine Learning
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    Chapter 23 Using Ontologies to Express Prior Knowledge for Genetic Programming
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    Chapter 24 Real Time Hand Movement Trajectory Tracking for Enhancing Dementia Screening in Ageing Deaf Signers of British Sign Language
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    Chapter 25 Commonsense Reasoning Using Theorem Proving and Machine Learning
Attention for Chapter 15: Differentially Private Obfuscation of Facial Images
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Chapter title
Differentially Private Obfuscation of Facial Images
Chapter number 15
Book title
Machine Learning and Knowledge Extraction
Published by
Springer, Cham, August 2019
DOI 10.1007/978-3-030-29726-8_15
Book ISBNs
978-3-03-029725-1, 978-3-03-029726-8
Authors

William L. Croft, Jörg-Rüdiger Sack, Wei Shi

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