ACML 2022 -- Second Call for Papers | OAMLS @ ACML

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Raj Sharma

May 13, 2022, 12:18:46 PMMay 13
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ACML 2022
The 14th Asian Conference on Machine Learning
Hyderabad, India
December 14-16, 2022


The 14th Asian Conference on Machine Learning (ACML 2022) will take place between December 14-16, 2022 at Hyderabad, India. The conference aims to provide a leading international forum for researchers in machine learning and related fields to share their new ideas, progress and achievements. While the main conference paper presentations will remain virtual to encourage widespread participation in current times, the conference will also have physical components to allow in-person interaction for those who can attend.

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. The conference runs two publication tracks: authors may submit either to the:
  1. conference track (16-page limit with references), for which the proceedings will be published as a volume of Proceedings of Machine Learning Research Workshop and Conference Proceedings (PMLR), or
  2. journal track (20-page limit with references) for which accepted papers will appear in a special issue of the Springer Machine Learning Journal (MLJ).

Please refer to for more details. Instructions for submission and LaTeX templates will be available soon (at least one month before the first deadline).

(subject to minor changes in case there are conflicts with timelines of other major ML conferences)

Conference Track
  • 23 Jun 2022 Submission deadline
  • 11 Aug 2022 Reviews released to authors
  • 18 Aug 2022 Author rebuttal deadline
  • 08 Sep 2022 Acceptance notification
  • 29 Sep 2022 Camera-ready submission deadline
Journal Track
  • 26 May 2022 Submission deadline
  • 07 Jul 2022 1st round review results (accept, minor revision, or reject)
  • 11 Aug 2022 Revised manuscript submission deadline (for minor revision papers)
  • 08 Sep 2022 Acceptance notification
  • 29 Sep 2022 Camera-ready submission deadline

TOPICS OF INTEREST include but are not limited to:

General machine learning
  • Active learning
  • Dimensionality reduction
  • Feature selection
  • Graphical models
  • Imitation Learning
  • Latent variable models
  • Learning for big data
  • Learning from noisy supervision
  • Learning in graphs
  • Multi-objective learning
  • Multiple instance learning
  • Multi-task learning
  • Online learning
  • Optimization
  • Reinforcement learning
  • Relational learning
  • Semi-supervised learning
  • Sparse learning
  • Structured output learning
  • Supervised learning
  • Transfer learning
  • Unsupervised learning
  • Other machine learning methodologies
Deep learning
  • Attention mechanism and transformers
  • Deep learning theory
  • Generative models
  • Deep reinforcement learning
  • Architectures
  • Other topics in deep learning
Probabilistic Methods
  • Bayesian machine learning
  • Graphical models
  • Variational inference
  • Gaussian processes
  • Monte Carlo methods
  • Computational learning theory
  • Optimization (convex, non-convex)
  • Bandits
  • Game theory
  • Matrix/Tensor methods
  • Statistical learning theory
  • Other theories
Datasets and Reproducibility
  • ML datasets and benchmarks
  • Implementations, libraries
  • Other topics in reproducible ML research
  • Trustworthy Machine Learning
  • Accountability/Explainability/Transparency
  • Causality
  • Fairness
  • Privacy
  • Robustness
  • Other topics in trustworthy ML
  • Bioinformatics
  • Biomedical informatics
  • Collaborative filtering
  • Computer vision
  • COVID-19 related research
  • Healthcare
  • Human activity recognition
  • Information retrieval
  • Natural language processing
  • Social networks
  • Web search
  • Climate science
  • Social good
  • Other applications

OAMLS @ ACML: Besides a program of tutorials and workshops, this year we will continue the Online Asian Machine Learning School (OAMLS) as part of ACML (dates to be finalized, likely to be around the ACML conference dates, held virtually). OAMLS aims to help prepare the next generation of machine learning researchers and practitioners by providing them with knowledge of machine learning fundamentals as well as state-of-the-art advances. It focuses on participants in the Asia-Pacific region; the virtual format, supported by ever-improving communication technologies, allows affordable participation from students and practitioners from a large part of the region, including those from under-represented areas, who may otherwise be unable to afford travel to a physical international school.
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