Workshop Talks

Workshop on Automatic Machine Learning

Automated machine learning (AutoML) is a rapidly growing field that develops algorithms and methods to automate the process of creating and optimizing machine learning models. It offers many benefits, faster development of process models, reduced expert-dependent costs, and increased efficiency.

Our workshop provides a platform for sharing results and experiences in automated machine learning. We invite researchers, developers and practitioners to discuss recent advances, challenges, and prospects in this field.

We encourage authors to improve the reproducibility of the results discussed in the workshop by publishing open source code and data as a supplementary material for each paper.

• To provide a platform for experts to share their latest research and developments in AutoML.
• To identify and discuss the challenges and opportunities for application of AutoML to real-world tasks.
• To foster collaboration and networking among researchers and practitioners in the field of AutoML
• To provide a forum for discussing ethical and societal implications of AI trustworthiness.

We are interested in papers that address the following topics:
  • Novel open-source AutoML tools
  • Optimization techniques for AutoML (evolutionary, Bayesian, reinforcement learning, etc)
  • Meta-Learning for AutoML
  • Neural Architecture Search (NAS)
  • Hyperparameter Optimization (HPO)
  • Feature selection and features engineering in AutoML
  • AutoML for the scientific and industrial applications
  • Reproducibility of the AutoML-related experiments
  • Benchmarking of AutoML

Abstract Registration Deadline:
The deadline for paper submissions is March 28, 2024.

Submission Deadline:
The deadline for paper submissions is April 3, 2024.

Notification of Acceptance:
Authors will be notified of acceptance by April 8, 2024.

Final paper submission Deadline:
Workshop final paper submission deadline is April 30, 2024.

Workshop Venue:
The workshop is collocated with the 12th conference on Artificial Intelligence and Natural Language (AINL 2024), and will be held on the 24th of April in Almaty, Kazakhstan.
Nikolay Nikitin: Automated machine learning: state-of-the-art and perspectives at the age of foundational models

Ivan Bondarenko: "I know that I know nothing": few words about uncertainty, pruning and architecture optimization in deep neural networks
If you have any questions about the workshop or the submission process, please contact the workshop's chair Sergey Muravyov at smuravyov@itmo.ru / mursmail@gmail.com

We look forward to receiving your submissions and welcoming you to the workshop.
Submission Guidelines
We invite the submission of papers that present original previously unpublished research. We accept short papers (6-11 pages) and full papers (12+ pages) formatted accordingly to the Springer LNCS style. Although Springer offers both LaTeX style files and Word templates, we highly encourage the authors to use LaTeX, especially for texts containing several formulæ. The papers must be written in English.

We use a double-blind review scheme. Please anonymize your papers when submitting for initial review.

At least one author of every accepted paper must register for the conference and present the paper offline (more preferably) or online.

The authors should use the EasyChair system to submit their papers:
Selected papers will be published in main conference proceedings and will be indexed by Scopus.
Sergey Muravyov, PhD, Head of CT Lab, ITMO University
Nikolay Nikitin, PhD, Head of AutoML Lab, Senior Researcher in NSS Lab, ITMO University
Alexey Zabashta, PhD, ITMO University