Willkommen, schön sind Sie da!
Logo Ex Libris

Machine Learning and Knowledge Extraction

  • Kartonierter Einband
  • 432 Seiten
(0) Erste Bewertung abgeben
Bewertungen
(0)
(0)
(0)
(0)
(0)
Alle Bewertungen ansehen
This book constitutes the refereed proceedings of the IFIP TC 5, TC 12, WG 8.4, 8.9, 12.9 International Cross-Domain Conference fo... Weiterlesen
20%
127.00 CHF 101.60
Sie sparen CHF 25.40
Print on Demand - Auslieferung erfolgt in der Regel innert 4 bis 6 Wochen.
Bestellung & Lieferung in eine Filiale möglich

Beschreibung

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.



Inhalt

KANDINSKY Patterns as IQ-Test for machine learning.- Machine Learning Explainability Through Comprehensible Decision Trees.- New Frontiers in Explainable AI: Understanding the GI to Interpret the GO.- Automated Machine Learning for Studying the Trade-off Between Predictive Accuracy and Interpretability.- Estimating the Driver Status Using Long Short Term Memory.- Using Relational Concept Networks for Explainable Decision Support.- Physiological Indicators for User Trust in Machine Learning with Influence Enhanced Fact-Checking.- Detection of Diabetic Retinopathy and Maculopathy in Eye Fundus Images Using Deep Learning and Image Augmentation.- Semi-automated Quality Assurance for Domain-expert-driven Data Exploration - An Application to Principal Component Analysis.- Ranked MSD: A New Feature Ranking and Feature Selection Approach for Biomarker Identification.- How to improve the adaptation phase of the CBR in the medical domain.- Machine Learning for Family Doctors: A Case of Cluster Analysis for studying Aging Associated Comorbidities and Frailty.- Knowledge Extraction for Cryptographic Algorithm Validation Test Vectors by Means of Combinatorial Coverage Measurement.- An Evaluation on Robustness and Utility of Fingerprinting Schemes.- Differentially Private Obfuscation of Facial Images.- Insights into Learning Competence through Probabilistic Graphical Models.- Sparse Nerves in Practice.- Backdoor Attacks in Neural Networks - a Systematic Evaluation on Multiple Traffic Sign Datasets.- Deep Learning for Proteomics Data for Feature Selection and Classification.- Package and Classify Wireless Product Features to Their Sales Items and Categories Automatically.- Temporal diagnosis of discrete-event systems with dual knowledge Compilation.- A Case for Guided Machine Learning.- Using Ontologies to Express Prior Knowledge for Genetic Programming.- Real Time Hand Movement Trajectory Tracking for Enhancing Dementia Screening in Ageing Deaf Signers of British Sign Language.- Commonsense Reasoning using Theorem Proving and Machine Learning.- Deep structured semantic model for recommendations with heterogeneous side information in e-commerce.

Produktinformationen

Titel: Machine Learning and Knowledge Extraction
Untertitel: 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
Editor:
EAN: 9783030297251
ISBN: 303029725X
Format: Kartonierter Einband
Herausgeber: Springer International Publishing
Anzahl Seiten: 432
Gewicht: 651g
Größe: H235mm x B155mm x T23mm
Jahr: 2019
Untertitel: Englisch
Auflage: 1st ed. 2019

Weitere Produkte aus der Reihe "Lecture Notes in Computer Science"