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Machine Learning and Knowledge Extraction

Third IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 International Cross-Domain Conference, CD-MAKE 2019, Canterbury, UK, August 26–29, 2019, Proceedings

  • Conference proceedings
  • © 2019

Overview

Editors:
  1. Andreas Holzinger

    1. Medical University of Graz, Graz, Austria

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  2. Peter Kieseberg

    1. St. Pölten University of Applied Sciences, St. Pölten, Austria

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  3. A Min Tjoa

    1. Vienna University of Technology, Vienna, Austria

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  4. Edgar Weippl

    1. SBA Research, Vienna, Austria

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 11713)

Part of the book sub series: Information Systems and Applications, incl. Internet/Web, and HCI (LNISA)

Included in the following conference series:

Conference proceedings info: CD-MAKE 2019.

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About this book

This book constitutes the refereed proceedings of the IFIP TC 5, TC 12, WG 8.4, 8.9, 12.9 International Cross-Domain Conference for Machine Learning and Knowledge Extraction, CD-MAKE 2019, held in Canterbury, UK, in August 2019.

The 25 revised full papers presented were carefully reviewed and selected from 45 submissions. The cross-domain integration and appraisal of different fields provides an atmosphere to foster different perspectives and opinions; it will offer a platform for novel ideas and a fresh look on the methodologies to put these ideas into business for the benefit of humanity.

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Table of contents (25 papers)

  1. Front Matter

    Pages i-xiii
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  2. KANDINSKY Patterns as IQ-Test for Machine Learning

    • Andreas Holzinger, Michael Kickmeier-Rust, Heimo Müller
    Pages 1-14

  3. Machine Learning Explainability Through Comprehensible Decision Trees

    • Alberto Blanco-Justicia, Josep Domingo-Ferrer
    Pages 15-26

  4. New Frontiers in Explainable AI: Understanding the GI to Interpret the GO

    • Federico Cabitza, Andrea Campagner, Davide Ciucci
    Pages 27-47

  5. Automated Machine Learning for Studying the Trade-Off Between Predictive Accuracy and Interpretability

    • Alex A. Freitas
    Pages 48-66

  6. Estimating the Driver Status Using Long Short Term Memory

    • Shokoufeh Monjezi Kouchak, Ashraf Gaffar
    Pages 67-77

  7. Using Relational Concept Networks for Explainable Decision Support

    • Jeroen Voogd, Paolo de Heer, Kim Veltman, Patrick Hanckmann, Jeroen van Lith
    Pages 78-93

  8. Physiological Indicators for User Trust in Machine Learning with Influence Enhanced Fact-Checking

    • Jianlong Zhou, Huaiwen Hu, Zhidong Li, Kun Yu, Fang Chen
    Pages 94-113

  9. Detection of Diabetic Retinopathy and Maculopathy in Eye Fundus Images Using Deep Learning and Image Augmentation

    • Sarni Suhaila Rahim, Vasile Palade, Ibrahim Almakky, Andreas Holzinger
    Pages 114-127

  10. Semi-automated Quality Assurance for Domain-Expert-Driven Data Exploration – An Application to Principal Component Analysis

    • Sandra Wartner, Manuela Wiesinger-Widi, Dominic Girardi, Dieter Furthner, Klaus Schmitt
    Pages 128-146

  11. Ranked MSD: A New Feature Ranking and Feature Selection Approach for Biomarker Identification

    • Ghanshyam Verma, Alokkumar Jha, Dietrich Rebholz-Schuhmann, Michael G. Madden
    Pages 147-167

  12. How to Improve the Adaptation Phase of the CBR in the Medical Domain

    • Ľudmila Pusztová, František Babič, Ján Paralič, Zuzana Paraličová
    Pages 168-177

  13. Machine Learning for Family Doctors: A Case of Cluster Analysis for Studying Aging Associated Comorbidities and Frailty

    • František Babič, Ljiljana Trtica Majnarić, Sanja Bekić, Andreas Holzinger
    Pages 178-194

  14. Knowledge Extraction for Cryptographic Algorithm Validation Test Vectors by Means of Combinatorial Coverage Measurement

    • Dimitris E. Simos, Bernhard Garn, Ludwig Kampel, D. Richard Kuhn, Raghu N. Kacker
    Pages 195-208

  15. An Evaluation on Robustness and Utility of Fingerprinting Schemes

    • Tanja Šarčević, Rudolf Mayer
    Pages 209-228

  16. Differentially Private Obfuscation of Facial Images

    • William L. Croft, Jörg-Rüdiger Sack, Wei Shi
    Pages 229-249

  17. Insights into Learning Competence Through Probabilistic Graphical Models

    • Anna Saranti, Behnam Taraghi, Martin Ebner, Andreas Holzinger
    Pages 250-271

  18. Sparse Nerves in Practice

    • Nello Blaser, Morten Brun
    Pages 272-284

  19. Backdoor Attacks in Neural Networks – A Systematic Evaluation on Multiple Traffic Sign Datasets

    • Huma Rehman, Andreas Ekelhart, Rudolf Mayer
    Pages 285-300

  20. Deep Learning for Proteomics Data for Feature Selection and Classification

    • Sahar Iravani, Tim O. F. Conrad
    Pages 301-316
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Other volumes

  1. Machine Learning and Knowledge Extraction

Editors and Affiliations

  • Medical University of Graz, Graz, Austria

    Andreas Holzinger

  • St. Pölten University of Applied Sciences, St. Pölten, Austria

    Peter Kieseberg

  • Vienna University of Technology, Vienna, Austria

    A Min Tjoa

  • SBA Research, Vienna, Austria

    Edgar Weippl

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