MLCI 2027

Sponsored by: University of the Ryukyus, Japan

Call for papers
Track 1: Foundations of Machine Learning
Supervised learning algorithms
Unsupervised learning techniques
Reinforcement learning frameworks and applications
Model selection, validation, and evaluation metrics
Probabilistic models and Bayesian methods
Optimization algorithms for machine learning

Track 2: Computational Intelligence Methods
Evolutionary computation
Fuzzy logic and fuzzy systems
Artificial neural networks
Swarm intelligence algorithms
Hybrid intelligent systems combining multiple computational intelligence techniques
Applications of computational intelligence in complex system modeling and optimization

Track 3: Advanced Machine Learning Systems
Deep learning architectures
Transfer learning and domain adaptation
Few-shot learning and meta-learning
Model deployment and scalability
Efficient training techniques
Applications in computer vision, natural language processing, and speech recognition

Track 4: Interdisciplinary Applications of ML and CI
Ethical considerations in AI and machine learning
Fairness, accountability, and transparency in algorithms
Explainable AI (XAI) and interpretability of machine learning models
Legal frameworks and regulations for AI
Future trends in machine learning and computational intelligence
Societal impact and sustainable development of AI technologies

Publication:
And accepted papers after proper registration and presentation, will be archived in the ACM Digital Library with Open Access, and submitted for indexing by Ei Compendex, Scopus, and other databases.

MLCI 2026 already published online: ACM (ISBN: 979-8-4007-2343-8) and indexed by Ei compendex and Scopus.

Submission
1. A regular submission must be at least full of 8 pages (including the title, authors, abstract, figures, and references). The extra page fee will be charged (60 USD) after 10 pages.
2. The submitted paper is requested to be written in complete English.