International Conference on Machine Learning and Computational Intelligence on April 18-20, 2026 in Ho Chi Minh City, Vietnam
- Event Type: Conference
- Presentation: Physical
- Website URL: https://www.icmlci.com/
- Program URL: https://www.icmlci.com/schedule.html
- Contact URL: https://www.icmlci.com/contact.html
- Contact E-mail: [email protected]
- Location: Ho Chi Minh City, Vietnam
- Date: April 18-20, 2026
- Final Submission: March 05, 2026
- Organization: The Asia Society of Researchers
- Conference Tags: machine intelligence machine vision machine learning virtual intelligence computational intelligence
Publication:
Accepted papers will be published by MLCI 2026 Conference Proceedings, indexed by Ei compendex and Scopus.
Submission:
1. Each paper should have no less than 4 pages normally, including all figures, tables, and references, extra page fee needs to be paid after 5 pages.
2. The submitted paper is requested to be written in complete English.
Full Paper Template: https://www.icmlci.com/Docx+Latex.zip
Abstract Template: https://www.icmlci.com/Abstract-Template.doc
Electronic Submission System Link:
https://www.zmeeting.org/submission/MLCI2026
Conference Venue:
Industrial University of Ho Chi Minh City, Vietnam
Address: 12 Nguyen Van Bao Street, Ward 4, Go Vap District, HCMC
Contact us:
Ms. Elisha Chen (Conference Secretary)
Email: [email protected]
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
Name: The Asia Society of Researchers
Website: http://www.asr.org/
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