Call for Sponsors

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

University of Hamburg, Germany
August 27 – August 30, 2018

to be held in conjunction with the 13th International Conference on Availability, Reliability and Security (ARES 2018) 

Call for Sponsors and Industrial Exhibitors

Corporate sponsorhip of the annual CD-MAKE conference contributes to the successful outcome of each year’s conference. The field of Artificial Intelligence generally, and Machine Learning specifically is highly relevant for Business and the official motto of our conference is the HCI-KDD leitmotiv “Science is to test crazy ideas – Engineering is to bring these ideas into business”. As such we encourage industry to take part, e.g. with exhibition spaces placed in prominent positions and visibility, but also to sponsor industrial workshops and events.

ABOUT CD-MAKE

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.

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 useable solutions for knowledge discovery and knowledge extraction.

CD-MAKE is co-located with the ARES Conference. Between 200 – 230 participants from more than 35 countries are attending ARES & CD-MAKE every year. ARES is organized by SBA Research, the largest research center in Austria that exclusively addresses information security. The conference was hold in various venues throughout Europe (previous conferences) and featured more than 30 well-known keynote speakers (previous keynotes).

SPONSOR PACKAGES:

The following sponsor packages are available for CD-MAKE 2018.

Bronze = 750 EUR (Logos, Flyer)
Silver = 1500 EUR (Bronze +  1 representative at the conference with table 1 sqm)
Gold = 3000 EUR (Silver + 1 standard exibition booth in a prominent place)
Platinum = individually negotiable and exhibition possibilities on demand (e.g. industry tutorial, workshop, etc., please check with the conference organizers)
Diamond = Platinum+beyond

Contact:

For details and questions, please contact Julia Pammer.

Bronze Sponsorship (EUR 750)

  • Flyers can be included in the conference bag
  • Listing of company name and logo on the conference website

Silver Sponsorship (EUR 1.500)

in addition to the Bronze Sponsorship benefits:

  • One free Conference Pass
  • Conference Table (1 sqm table top)

Gold Sponsorship (EUR 3.000)

in addition to the Silver Sponsorhsip benefits:

  • One free Conference Pass
  • Conference Booth (standard exhibition booth in high traffic area during the Conference Days)
  • Acknowledgement in the General Chair’s statement in the Conference Proceedings