The 10th Asian Conference on Machine Learning, Beijing

Beijing Jiaotong University
November 14 - 16, 2018

ACML 2018

Welcome to the 10th Asian Conference on Machine Learning (ACML 2018). The conference will take place on November 14 - 16, 2018 at Beijing Jiaotong University, Beijing, China. 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. ACML has begun to take place annually over the Asian regions since 2009. This is the 10th Conference to be held in Beijing, China after Seoul, Korea (2017), Hamilton, New Zealand (2016), Hong Kong, China (2015), Nha Trang, Vietnam (2014), Canberra, Australia (2013), Singapore (2012), Taoyuan, Taiwan (2011), Tokyo, Japan (2010), and Nanjing, China (2009).

Following last year, we are also running two publication tracks in this year: Authors may submit either to the conference track, for which the proceedings will be published as a volume of Proceedings of Machine Learning Research (PMLR) series, or to the journal track for which accepted papers will appear in a special issue of the Springer journal Machine Learning.

Important Dates

Journal Track Early Submission Deadline: February 28, 2018
Journal Track Final Submission Deadline: March 31, 2018 April 20, 2018
Workshop and Tutorial Proposals Deadline: May 10, 2018
Conference Track Early Submission Deadline:May 10, 2018
Conference Track Early Notification Date: June 20, 2018
Conference Track Final Submission Deadline:August 1, 2018
Conference Track Final Notification Date:September 20, 2018
Conference Track Final Manuscript Deadline:October 5, 2018

All deadlines are 11:59pm Pacific Standard Time (PST)

Hosts

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