*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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- Towards Augmenting Human Intelligence with Artificial Intelligence -
-----------------------------------------------------------------------
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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