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.