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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

Aus der Reihe Lecture Notes in Computer Science

Fr. 142.00

inkl. gesetzl. MwSt., Versandkostenfrei

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

21.08.2020

Herausgeber

Andreas Holzinger + weitere

Verlag

Springer

Seitenzahl

552

Maße (L/B/H)

23.5/15.5/3.1 cm

Gewicht

844 g

Auflage

1st ed. 2020

Sprache

Englisch

ISBN

978-3-030-57320-1

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

21.08.2020

Herausgeber

Verlag

Springer

Seitenzahl

552

Maße (L/B/H)

23.5/15.5/3.1 cm

Gewicht

844 g

Auflage

1st ed. 2020

Sprache

Englisch

ISBN

978-3-030-57320-1

Herstelleradresse

Springer-Verlag KG
Sachsenplatz 4-6
1201 Wien
AT

Email: GPSR Kontakt

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  • Produktbild: Machine Learning and Knowledge Extraction
  • Produktbild: Machine Learning and Knowledge Extraction

  • 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: Impactof 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.