| Issue |
ITM Web Conf.
Volume 81, 2026
International Conference on Emerging Technologies for Multidisciplinary Innovation and Sustainability (ETMIS 2025)
|
|
|---|---|---|
| Article Number | 01023 | |
| Number of page(s) | 7 | |
| DOI | https://doi.org/10.1051/itmconf/20268101023 | |
| Published online | 23 January 2026 | |
A Comprehensive Review of VertexML: A Model Training Platform
Department of Computer Science and Engineering (AI&ML), Malnad College of Engineering, Hassan 573202, India
* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.
This paper presents a comprehensive survey of automated machine learning (AutoML) techniques, with a focus on meta-learning, hyperparameter optimization, and neural architecture search (NAS). Rather than proposing or evaluating a full AutoML platform, this work synthesizes insights from 49 influential research papers, organizing them into methodological categories and highlighting their contributions to the evolution of ML automation. The survey also analyzes trends across model types, optimization strategies, and publication patterns. Based on this review, the paper identifies research gaps and outlines key directions for future development of unified, scalable, and interpretable AutoML systems. This survey is intended to provide a structured foundation for researchers working toward improved ML automation pipelines.
© The Authors, published by EDP Sciences, 2026
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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