Call for Papers 2018

International IFIP Cross Domain Conference for Machine Learning & Knowledge Extraction CD-MAKE
in Hamburg (Germany) August 27 – 30, 2018

CD stands for Cross-Domain and means the integration and appraisal of different fields and application domains (e.g. Health, Industry 4.0, etc.) to provide an atmosphere to foster different perspectives and opinions. The conference is dedicated to offer an international platform for novel ideas and a fresh look on the methodologies to put crazy ideas into Business for the benefit of the human. Serendipity is a desired effect, and shall cross-fertilize methodologies and transfer of algorithmic developments.

MAKE stands for MAchine Learning & Knowledge Extraction.

CD-MAKE is a joint effort of IFIP TC 5, IFIP WG 8.4, IFIP WG 8.9 and IFIP WG 12.9 and is held in conjunction with the International Conference on Availability, Reliability and Security (ARES).
Keynote Speakers are Neil D. LAWRENCE (Amazon) and Marta MILO (University of Sheffield).

IFIP is the International Federation for Information Processing and the leading multi-national, non-governmental, apolitical organization in Information & Communications Technologies and Computer Sciences, is recognized by the United Nations and was established in the year 1960 under the auspices of the UNESCO as an outcome of the first World Computer Congress held in Paris in 1959.

Papers are sought from the following seven topical areas (see image below). Papers which deal with fundamental questions and theoretical aspects in machine learning are very welcome.

❶ Data science (data fusion, preprocessing, data mapping, knowledge representation),
❷ Machine learning (both automatic ML and interactive ML with the human-in-the-loop),
❸ Graphs/network science (i.e. graph-based data mining),
❹ Topological data analysis (i.e. topology data mining),
❺ Time/entropy (i.e. entropy-based data mining),
❻ Data visualization (i.e. visual analytics), and last but not least
❼ Privacy, data protection, safety and security (i.e. privacy aware machine learning).

Proposals for Workshops, Special Sessions, Tutorials: tba
Submission Deadline: tba
Author Notification: tba
Camera Ready Deadline: tba

Accepted Papers will be published in a Springer Volume of Lecture Notes in Artificial Intelligence (LNAI). Outstanding contributions will be invited to special issues of journals. Currently the following journals are planned (under construction – list not yet complete):

Successful machine learning needs a concerted effort supporting the whole Knowledge Extraction/Discovery Pipeline! Machine learning must be directly in the workflow from preprocessing to visualization!