Call for Papers (pdf)

Call for Papers

Final submission deadline extended to August 6th.

The 4th Asian Conference on Machine Learning (ACML2012) will be held on November 4-6, 2012, at the Singapore Management University, Singapore. The conference aims at providing a leading international forum for researchers in machine learning and related fields to share their new ideas and achievements. Submissions from other than the Asia-Pacific regions are also highly encouraged. The conference calls for research papers reporting original investigation results. The conference also solicits proposals focusing on frontier research in all aspects of machine learning.

The proceedings will be published as a volume of Journal of Machine Learning Research (JMLR): Workshop and Conference Proceedings. Authors of selected papers will be invited to submit a significantly extended version of their paper to a post-conference special issue of the Machine Learning journal. The best student paper will receive an award sponsored by the Machine Learning journal.

This year ACML will have a new feature: two submission deadlines. The late deadline has the usual “accept” or “reject” outcomes. In addition to the two outcomes, the early deadline also has "conditional accept subject to required revisions", and “resubmit” with notification in time for them to make the final deadline. The submission of "conditional accept" decision is strongly encouraged to carefully address the review comments in their revision. The revision without addressing the review comments properly might be rejected. The submission of "resubmit" decision must be significantly improved and revised before it can be re-submitted in the late deadline. Fresh submissions that have not caught up with the early deadline are also welcome for the late deadline.

For questions and suggestions on paper submission, please write to:

Important Dates

Early Paper Submission: 8 May
Early Notification: 24 June
Final Paper Submission: 24 July Extended to 6 August
Final Notification: 8 Sept
Camera ready: 24 Sept
Conference: November 4-6, 2012

Topics of Interest

Topics of interest include but are not limited to:

1. Learning problems

  • Active learning
  • Cost-sensitive Learning
  • Ensemble methods
  • Feature selection/extraction/construction
  • Incremental learning and on-line learning
  • Learning in graphs and networks
  • Multi-agent learning
  • Multi-instance learning
  • Reinforcement learning
  • Semi-supervised learning
  • Supervised learning
  • Classification, regression, ranking, structured, logical
  • Transfer and multi-task learning
  • Unsupervised learning
  • Clustering, deep learning, latent variable models
  • Other learning problems

2. Analysis of learning systems

  • Computational learning theory
  • Statistical learning theory
  • Experimental evaluation methodology
  • Others

3. Applications

  • Bioinformatics
  • Collaborative filtering
  • Computer vision
  • Information retrieval
  • Mobile and pervasive computing
  • Natural language processing
  • Social networks
  • Web search
  • Other applications

4. Learning in knowledge-intensive systems

  • Knowledge refinement and theory revision
  • Multi-strategy learning
  • Other systems

5. Other learning problems

Paper Submission

Paper should be submitted through the ACML 2012 submission site: Each submission should be regarded as an undertaking that, if the paper is accepted, at least one of the authors must attend the conference to present the work. No-show papers will not be included in the proceedings.

Paper Format

Papers should be written in English and formatted according to the JMLR Workshop and Conference Proceedings format ( The maximum length of papers is 16 pages in this format. Overlength submissions or submissions without appropriate format will be rejected without review. Paper submissions should ensure double-blind reviews. Please be sure to remove any information from your submission that can identify the authors, including author names, affiliations, self citations and any acknowledgments.

Proceedings will be published as a volume of JMLR: Workshop and Conference Proceedings (this is not equivalent to a regular issue of JMLR) at Please download the file for the LaTex template and style file (the files are extracted from - you may also download and use the entire package from there). Only the LaTex preparation system is supported to allow publication in the JMLR: Workshop and Conference Proceedings series.

Policy on Dual Submission

ACML allows concurrent submissions to other venues provided that

  1. The concurrent submission is declared to all venues.
  2. Permission is given by the author(s) for ACML to coordinate reviewing with the other venues.
  3. Acceptance to one venue imposes withdrawal from all other venues.

It is also acceptable to submit to ACML 2012 work that has been made available as a technical report (or similar, e.g. in arXiv) as long as the conditions above are satisfied.

Supplementary Material

ACML 2012 supports the submission of supplementary material, such as additional/detailed proofs, source/binary code, videos, or data sets. In particular, if you make anonymous references in your submitted paper, please upload the referenced papers so that the reviewers could have a look of them. Note that you cannot reveal your identity in the supplementary material.

It important to note that the submitted papers must be self-contained. Reviewers are encouraged, but not obliged to look at the provided supplementary material. That is, you must not use supplementary material for extending the length of your paper. If there is any material that you believe is critical to the evaluation of your paper, you must include them in the submitted paper.

Finally, the supplementary material will not be published or archived by ACML. If you want to include it in a final version of the accepted paper, you must put it on a web site and reference the site in the final version of your paper.

Review Process

Each paper will be rigorously reviewed by at least three reviewers.The paper review process is double-blind.