to be held in conjunction with
December 11-14th, 2018
Wellington, New Zealand
With more and more big data, parallel and distributed computing is increasingly more demanding for AI and machine learning practitioners. Taking advantage of parallel and distributed computing can increase the speed of AI and machine learning algorithms, and solve a big data problem with a feasible and better solution.
This workshop will bring together researchers in parallel and distributed computing, machine learning, and artificial intelligence to discuss state-of-the-art parallelization techniques for AI and machine learning algorithms, identify critical big data and AI applications demanding parallelization, and promote parallel and distributed computing among AI practitioners and domain experts.
Paper submission deadline :
August 27, 2018 extended to September 24, 2018 (Anywhere On Earth)
Notification of acceptance : October 12, 2018
Camera-ready papers due : October 26, 2018
The program committee cordially invites any novel research ideas in (but not limited to) the following topics:
Shanghai Jiaotong University, China
chen-quan at cs dot sjtu dot edu dot cn
University of Otago, New Zealand
hzy at cs dot otago dot ac dot nz
Papers reporting original and unpublished research results and experience are solicited. All paper submissions will be handled electronically via EasyChair.
Papers must not exceed 8 pages in double-column ACM sigconf style. Templates for the ACM sigconf style are available at here.
Authors must register and submit their paper through the online submission system.
If you have problems accessing the system, e-mail your submission to:
pamla2018 at cs dot otago dot ac dot nz
All accepted papers will be published in the a joint Proceedings of AI Workshops to be published by ACM (approved).
Information about registration can be found at AI 2018 website.
For further information regarding the workshop and paper submission, please send your request or enquiry to: pamla2018 at cs dot otago dot ac dot nz