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Date: Thu, 22 Feb 2018 07:03:22 +0100
Reply-To: Andreas Holzinger <[log in to unmask]>
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*Call for Papers*

International IFIP CD MAKE 2018 Cross Domain Conference for Machine 
Learning & Knowledge Extraction

Hamburg, August 27 – 30, 2018

CD-MAKE is a joint effort of IFIP*) TC 5 (Information Technology 
Applications), TC 12 (Artificial Intelligence), IFIP WG 8.4 (E-Business: 
Multi-disciplinary research and practice), IFIP WG 8.9 (Enterprise 
Information Systems) and IFIP WG 12.9 (Computational Intelligence) and 
is held in conjunction with the International Conference on 
Availability, Reliability and Security (ARES).

Motto of CD-MAKE: Augmenting Human Intelligence with Artificial Intelligence

Goal of CD-MAKE: To act as a Catalyst to bring together researchers in 
an cross-disciplinary manner, to stimulate fresh ideas and to encourage 
multi-disciplinary problem solving in the area of AI and machine learning.

Submissions due to April, 01, 2018
Springer LNCS camera ready deadline June, 27, 2018

https://cd-make.net

CD stands for Cross-Domain and means the integration and appraisal of 
seemingly disparate fields (e.g. algebraic topology, entropy, geometry, 
etc.) and different application domains (e.g. Health, Industry 4.0, AAL, 
etc.) to provide an atmosphere to foster different perspectives and 
opinions. The conference is dedicated to offer an international platform 
without any boundaries for novel ideas and a fresh look on the 
methodologies to put crazy ideas into Business for the benefit of 
society. Serendipity is a desired effect, and shall cross-fertilize 
methodologies and transfer of algorithmic developments.

MAKE stands for MAchine Learning & Knowledge Extraction.

Machine learning deals with understanding intelligence for the design 
and development of algorithms that can learn from data and improve over 
time. The original definition was “the artificial generation of 
knowledge from experience”. The challenge is to discover relevant 
structural patterns and/or temporal patterns (“knowledge”) in such data, 
which are often hidden and not accessible to a human. Today, machine 
learning is the fastest growing technical field, having many application 
domains, e.g. health, Industry 4.0, recommender systems, speech 
recognition, autonomous driving, etc. The challenge is in decision 
making under uncertainty, and probabilistic inference enormously 
influenced artificial intelligence and statistical learning. The inverse 
probability allows to infer unknowns, learn from data and make 
predictions to support decision making. Whether in social networks, 
recommender systems, health or Industry 4.0 applications, the 
increasingly complex data sets require efficient, useful and usable 
solutions for knowledge discovery and knowledge extraction.

A synergistic combination of methodologies and approaches of two domains 
offer ideal conditions towards unraveling these challenges and to foster 
new, efficient and user-friendly machine learning algorithms and 
knowledge extraction tools: Human-Computer Interaction (HCI) and 
Knowledge Discovery/Data Mining (KDD), aiming at augmenting human 
intelligence with computational intelligence and vice versa.

Consequently, successful Machine Learning & Knowledge extraction needs a 
concerted international effort without boundaries, supporting 
collaborative and integrative cross-disciplinary research between 
experts from diverse areas.

*) IFIP - the International Federation for Information Processing is the 
leading multi-national, non-governmental, apolitical organization in 
Information & Communications Technologies and Computer Sciences, is 
recognized by the United Nations (UN) 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.

- Towards Augmenting Human Intelligence  with Artificial Intelligence -
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Assoc.Prof. Dr. Andreas HOLZINGER, Group Leader, Research Unit, HCI-KDD
Institute for Medical Informatics / Statistics, Medical University Graz
Auenbruggerplatz 2/V,  A-8036 Graz, AUSTRIA,  Phone: ++43 316 385 13883
Group Homepage: http://hci-kdd.org   Personal: http://www.aholzinger.at
MAKE Conf: https://cd-make.net  3-Min MAKE Video: https://goo.gl/0hcPOY
Visiting Prof. for Machine Learning in Health Informatics at  TU Vienna
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Science is testing crazy ideas - Engineering is bringing it to Business

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