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The 11th Asian Conference on Machine Learning (ACML 2019) will take place on November 17 - 19, 2019 at WINC AICHI, Nagoya, Japan. The conference aims to provide a leading international forum for researchers in machine learning and related fields to share their new ideas, progresses and achievements. Submissions from regions other than the Asia-Pacific are also highly encouraged.
The conference calls for high-quality, original research papers in the theory and practice of machine learning. The conference also solicits proposals focusing on frontier research, new ideas and paradigms in machine learning. We encourage submissions from all parts of the world, not only confined to the Asia-Pacific region.
This year we are running two publication tracks: Authors may submit either to the conference track, for which the proceedings will be published as a volume of Proceedings of Machine Learning Research Workshop and Conference Proceedings (PMLR), or to the journal track for which accepted papers will appear in a special issue of the Springer journal Machine Learning (MLJ).
ACML2019 Website: http://www.acml-conf.org/2019/
ACML2019 CFP: http://www.acml-conf.org/2019/calls/papers/
Important Dates
(Journal Track: the accepted papers will be published from Machine Learning Journal)
**Deadline is extended**
May.03, 2019: Paper Submission Deadline
Jun.15, 2019: Review Result Released (Accept, Minor Revision, or Reject)
Jul.15, 2019: Revision Submission Deadline
Sep.03, 2019: Notification (Accept or Reject)
Sep.30, 2019: Camera-Ready Submission Deadline
(Conference Track: the accepted papers will be published from Proceedings of Machine Learning Research)
Conference track 1st round
Apr.15, 2019: Submission Deadline
May.30, 2019: Notification (Accept, Reject, or Encourage Resubmission to 2nd Round)
Sep.30, 2019: Camera-Ready Submission Deadline
Conference track 2nd round
Jul.15, 2019: Submission Deadline
Aug.19, 2019 - Aug.24, 2019: Author Rebuttal
Sep.03, 2019: Notification (Accept or Reject)
Sep.30, 2019: Camera-Ready Submission Deadline
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