Machine Learning and Knowledge Extraction

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.