Full name: 2026 The 9th International Conference on Machine Learning and Machine Intelligence (MLMI 2026)

Abbreviation: MLMI 2026

Tokyo, Japan

July 17-20, 2026

Publication

Option 1: 

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.

Option 2: 

All papers will be strictly double blind reviewed by the program committee, and accepted papers after proper registration and presentation will be published in the International Conference Proceedings Series by ACM (ISBN: 979-8-4007-2468-8), which will be archived in the ACM Digital Library, and indexed by Ei Compendex, Scopus, etc.

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

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)

Keynote&Invited Speakers:
Prof. Dapeng Wu (IEEE Fellow), City University of Hong Kong, Hong Kong, China
Prof. Xudong Jiang (IEEE Fellow), Nanyang Technological University, Singapore
Prof. Minghua Chen (IEEE Fellow), The Chinese University of Hong Kong, Shenzhen, China
Prof. Farshid Alizadeh-Shabdiz, Boston University, USA