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UID:122-409@gi.de
CLASS: PUBLIC
SUMMARY:Cross Domain Conference for Machine Learning and Knowledge Extracti
 on
DESCRIPTION:The International Cross Domain Conference for Machine Learning 
 & Knowledge Extraction CD-MAKE\n\nis a joint effort of IFIP TC 5 (Informati
 on Technology Applictions), TC 12 (Artificial Intelligence), IFIP WG 8.4 (E
 -Business: Multi-disciplinary research and practice), IFIP WG 8.9 (Enterpri
 se Information Systems) and IFIP WG 12.9 (Computational Intelligence) and i
 s held in conjunction with the International Conference on Availability, Re
 liability and Security (ARES).\n\nCD 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 p
 erspectives and opinions. The conference is dedicated to offer an internati
 onal 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 de
 sired effect, and shall cross-fertilize methodologies and transfer of algor
 ithmic developments.\n\nMAKE stands for MAchine Learning & Knowledge Extrac
 tion.\n\nMachine learning deals with understanding intelligence for the des
 ign 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 hidde
 n and not accessible to a human. Today, machine learning is the fastest gro
 wing technical field, having many application domains, e.g. health, Industr
 y 4.0, recommender systems, speech recognition, autonomous driving, etc. Th
 e challenge is in decision making under uncertainty, and probabilistic infe
 rence enormously influenced artificial intelligence and statistical learnin
 g. The inverse probability allows to infer unknowns, learn from data and ma
 ke predictions to support decision making. Whether in social networks, reco
 mmender systems, health or Industry 4.0 applications, the increasingly comp
 lex data sets require efficient, useful and useable solutions for knowledge
  discovery and knowledge extraction.\n\nA synergistic combination of method
 ologies and approaches of two domains offer ideal conditions towards unrave
 ling these challenges and to foster new, efficient and user-friendly machin
 e learning algorithms and knowledge extraction tools: Human-Computer Intera
 ction (HCI) and Knowledge Discovery/Data Mining (KDD), aiming at augmenting
  human intelligence with computational intelligence and vice versa.
LOCATION:https://cd-make.net/
DTSTAMP:20180116T114207Z
DTSTART:20180827T070000Z
DTEND:20180830T150000Z
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