Full name: 2026 The 9th International Conference on Machine Learning and Machine Intelligence (MLMI 2026)
Abbreviation: MLMI 2026
Tokyo, Japan
July 17-20, 2026
Website: http://mlmi.net/
Publication:
Submitted papers will be peer reviewed by conference committees, and accepted papers after proper registration and presentation will be published into Lecture Notes in Electrical Engineering (Electronic ISSN: 1876-1119 & Print ISSN: 1876-1100) as a proceedings book volume. The book series will be indexed by EI Compendex, SCOPUS, INSPEC, SCImago and other database.
MLMI 2024 conference proceedings (ISBN: 979-8-4007-1783-3) - ACM Digital Library | Ei Compendex | Scopus
MLMI 2023 conference proceedings (ISBN: 979-8-4007-0945-6) - ACM Digital Library | Ei Compendex | Scopus
MLMI 2022 conference proceedings (ISBN: 978-1-4503-9755-1) - ACM Digital Library | Ei Compendex | Scopus
MLMI 2021 conference proceedings (ISBN: 978-1-4503-8424-7) - ACM Digital Library | Ei Compendex | Scopus
MLMI 2020 conference proceedings (ISBN: 978-1-4503-8834-4) - ACM Digital Library | Ei Compendex | Scopus
MLMI 2019 conference proceedings (ISBN: 978-1-4503-7248-0) - ACM Digital Library | Ei Compendex | Scopus
MLMI 2018 conference proceedings (ISBN: 978-1-4503-6556-7) - ACM Digital Library | Ei Compendex | Scopus
Topics:
Topics of interest for submission include, but are not limited to:
Track 1: Deep Learning and Neural Architectures
Neural Architecture Search
Generative Models
Transfer Learning
Track 2: Reinforcement Learning and Sequential Decision Making
Multi-Agent Reinforcement Learning
Time Series and Sequential Data
Real-Time AI Systems
Track 3: Applied Machine Intelligence
Machine Learning in Healthcare
AI in Robotics
Biometric and Behavioral Analytics
Track 4: Natural Language Processing and Multimodal Learning
Large Language Models
Multilingual and Low-Resource NLP
Cross-Modal Retrieval and Generation
Track 5: Emerging Paradigms and Future Directions
Quantum Machine Learning
Federated and Distributed Learning
AutoML and Meta-Learning
Track 6: Explainable, Ethical, and Human-Centered AI
Explainable AI (XAI)
Ethical AI and Fairness
Privacy-Preserving Machine Learning
For more topics, please visit: http://www.mlmi.net/cfp.html
Submission Guideline:
1. English is the official language. Paper should be prepared in English.
2. Abstract submission is for presentation only without publication.
3. Full paper submission is for both presentation and publication. (No less than 10 pages)
4. Submission Methods:
- By online submission system: http://confsys.iconf.org/submission/mlmi2026
- Or Submit to mlmi_contact@163.com as attachment
For more details, please visit: http://www.mlmi.net/submission.html
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