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 25-2...

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Titel
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
verantwortlich
Holzinger, Andreas.; Kieseberg, Peter.; Tjoa, A Min.; Weippl, Edgar R.; IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 International Cross-Domain Conference (4th : 2020 : Online)
Schriftenreihe
Lecture notes in computer science ; ; 12279
veröffentlicht
Cham, Switzerland: Springer, 2020
Erscheinungsjahr
2020
Teil von
Lecture notes in computer science ; ; 12279.
Teil von
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Datenquelle
British National Bibliography
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Inhaltsangabe:
  • 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 Co llaboration: 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.