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Machine Learning and Knowledge Extraction
4th IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 International Cross-Domain Conference, CD-MAKE 2020, Dublin, Ireland, August 25-28, 2020, Proceedings
1 online resource (XI, 552 pages 171 illustrations, 112 illustrations in color.)
This book constitutes the refereed proceedings of the 4th IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 International Cross-Domain Conference, CD-MAKE 2020, held in Dublin, Ireland, in August 2020. The 30 revised full papers presented were carefully reviewed and selected from 140 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. Due to the Corona pandemic CD-MAKE 2020 was held as a virtual event.
Explainable Artificial Intelligence: concepts, applications, research challenges and visions -- The Explanation Game: Explaining Machine Learning Models Using Shapley Values -- Back to the Feature: a Neural-Symbolic Perspective on Explainable AI -- Explain Graph Neural Networks to Understand Weighted Graph Features in Node Classification -- Explainable Reinforcement Learning: A Survey -- A Projected Stochastic Gradient algorithm for estimating Shapley Value applied in attribute importance -- Explaining predictive models with mixed features using Shapley values and conditional inference trees -- Explainable Deep Learning for Fault Prognostics in Complex Systems: A Particle Accelerator Use-Case -- eXDiL: A Tool for Classifying and eXplaining Hospital Discharge Letters -- Data Understanding and Interpretation by the Cooperation of Data Analyst and Medical Expert -- A study on the fusion of pixels and patient metadata in CNN-based classification of skin lesion images -- The European legal framework for medical AI -- An Efficient Method for Mining Informative Association Rules in Knowledge Extraction -- Interpretation of SVM using Data Mining Technique to Extract Syllogistic Rules -- Non-Local Second-Order Attention Network For Single Image Super Resolution -- ML-ModelExplorer: An explorative model-agnostic approach to evaluate and compare multi-class classifiers -- Subverting Network Intrusion Detection: Crafting Adversarial Examples Accounting for Domain-Specific Constraints -- Scenario-based Requirements Elicitation for User-Centric Explainable AI A Case in Fraud Detection -- On-the-fly Black-Box Probably Approximately Correct Checking of Recurrent Neural Networks -- Active Learning for Auditory Hierarchy -- Improving short text classification through global augmentation methods -- Interpretable Topic Extraction and Word Embedding Learning using row-stochastic DEDICOM -- A Clustering Backed Deep Learning Approach for Document Layout Analysis -- Calibrating Human-AI Collaboration: Impact of Risk, Ambiguity and Transparency on Algorithmic Bias -- Applying AI in Practice: Key Challenges and Lessons Learned -- Function Space Pooling For Graph Convolutional Networks -- Analysis of optical brain signals using connectivity graph networks -- Property-Based Testing for Parameter Learning of Probabilistic Graphical Models -- An Ensemble Interpretable Machine Learning Scheme for Securing Data Quality at the Edge -- Inter-Space Machine Learning in Smart Environments.
edited by Andreas Holzinger, Peter Kieseberg, A Min Tjoa, Edgar Weippl.
Computer Imaging, Vision, Pattern Recognition and Graphics
Software Engineering/Programming and Operating Systems
Information Systems and Applications, incl. Internet/Web, and HCI ; 12279