Machine learning and Knowledge Extraction (MAKE) is the workhorse of Artificial Intelligence (AI). Successful human-centered AI needs a concerted effort without boundaries, supporting collaborative and integrative cross-disciplinary research between experts cross-domain.

The goal of the CD-MAKE conference is to act as a catalysator, to bring together academia and industry in a cross-disciplinary manner, to stimulate fresh ideas and to support human-centered AI:

❶ DATA – data fusion, preprocessing, mapping, knowledge representation, discovery
❷ LEARNING – algorithms, contextual adaptation, explainable-AI, causal reasoning
❸ VISUALIZATION – visual analytics, intelligent interfaces, human-computer interaction
❹ PRIVACY – data protection, safety, security, ethics, acceptance and social issues of ML
❺ NETWORK – graphical models, graph-based machine learning
❻ TOPOLOGY – geometrical machine learning, topological and manifold learning
❼ ENTROPY – time and machine learning, entropy-based ML