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

AvAndreas Holzinger,Peter Kieseberg

Häftad, Engelska, 2020

Del 12279 i serien Lecture Notes in Computer Science

1 139 kr

Beställningsvara. Skickas inom 10-15 vardagar. Fri frakt över 249 kr.

Beskrivning

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.

Produktinformation

Utgivningsdatum:2020-08-21
Mått:155 x 235 x 32 mm
Vikt:830 g
Format:Häftad
Språk:Engelska
Serie:Lecture Notes in Computer Science
Antal sidor:552
Upplaga:20001
Förlag:Springer Nature Switzerland AG
ISBN:9783030573201

Utforska kategorier

Innehållsförteckning

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.

Du kanske också är intresserad av

Nyhet

Exit Adventskalender - Julens magi (SE)

Exit

499 kr

Del 14065

Machine Learning and Knowledge Extraction

Andreas Holzinger, Peter Kieseberg, Federico Cabitza, Andrea Campagner, A Min Tjoa, Edgar Weippl

Häftad, 2023

629 kr

Machine Learning and Knowledge Extraction

Edgar Weippl, A Min Tjoa, Peter Kieseberg, Andreas Holzinger

E-bok

2022

1 292 kr

Machine Learning and Knowledge Extraction

Edgar Weippl, A Min Tjoa, Andrea Campagner, Federico Cabitza, Peter Kieseberg, Andreas Holzinger

E-bok

2023

821 kr

Del 11713

Machine Learning and Knowledge Extraction

Andreas Holzinger, Peter Kieseberg, A Min Tjoa, Edgar Weippl

Häftad, 2019

572 kr

Machine Learning and Knowledge Extraction

Edgar Weippl, A Min Tjoa, Peter Kieseberg, Andreas Holzinger

E-bok

2021

1 387 kr

Machine Learning and Knowledge Extraction

Edgar Weippl, A Min Tjoa, Peter Kieseberg, Andreas Holzinger

E-bok

2018

718 kr

Francesco Buccafurri, Andreas Holzinger, Peter Kieseberg, A Min Tjoa, Edgar Weippl - Availability, Reliability, and Security in Information Systems, Häftad

Del 9817

Availability, Reliability, and Security in Information Systems

Francesco Buccafurri, Andreas Holzinger, Peter Kieseberg, A Min Tjoa, Edgar Weippl

Häftad, 2016

572 kr

Del 12844

Machine Learning and Knowledge Extraction

Andreas Holzinger, Peter Kieseberg, A Min Tjoa, Edgar Weippl

Häftad, 2021

1 073 kr

Del 13480

Machine Learning and Knowledge Extraction

Andreas Holzinger, Peter Kieseberg, A Min Tjoa, Edgar Weippl

Häftad, 2022

1 024 kr

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

AvAndreas Holzinger,Peter Kieseberg

Häftad, Engelska, 2020

Del 12279 i serien Lecture Notes in Computer Science

1 139 kr

Beställningsvara. Skickas inom 10-15 vardagar. Fri frakt över 249 kr.

Beskrivning

Produktinformation

Utgivningsdatum:2020-08-21
Mått:155 x 235 x 32 mm
Vikt:830 g
Format:Häftad
Språk:Engelska
Serie:Lecture Notes in Computer Science
Antal sidor:552
Upplaga:20001
Förlag:Springer Nature Switzerland AG
ISBN:9783030573201

Utforska kategorier

Innehållsförteckning

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.