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
Keynote Speakers:
Prof. Zhihua Zhou (IEEE/ACM/AAAI/AAAS Fellow, member of the Academia Europaea)
Nanjing University, China
Prof. Ryuji Kohno (IEICE Life/IEEE Fellow)
Yokohama National University, Japan
Prof. Guoping Qiu
The University of Nottingham, UK & The University of Nottingham Ningbo, China
Invited Speakers:
Prof. Antonio Alarcón-Paredes
National Polytechnic Institute, Mexico
Prof. Abril Uriarte Arcia
CIDETEC - IPN, Mexico
Asst. Prof. Isaac Kofi Nti
University of Cincinnati, USA
Assoc. Prof. Jiaxin Cai
Xiamen University of Technology, China
Dr. Vishnu S. Pendyala
San Jose State University, USA
Topics:
Topics of interest for submission include, but are not limited to:
Track 1: Deep Learning and Neural Architectures
-Architectural Advances
-Efficient Training Techniques
Track 2: Reinforcement Learning and Sequential Decision Making
-Advanced Reinforcement Learning Algorithms
-Multi-Agent Reinforcement Learning
Track 3: Applied Machine Intelligence
-Machine Learning in Healthcare
-AI in Robotics
Track 4: Natural Language Processing and Multimodal Learning
-Large Language Models
-Multilingual and Low-Resource NLP
Track 5: Emerging Paradigms and Future Directions
-Quantum Machine Learning
-Federated and Distributed Learning
Track 6: Explainable, Ethical, and Human-Centered AI
-Explainable AI (XAI)
-Ethical AI and Fairness
Contact Us:
Conference Secretary: Miss Joie Wu
Email: mlmi_contact@163.com
Tel: +86-18302820449
Website: http://mlmi.net/
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
Keynote Speakers:
Prof. Zhihua Zhou (IEEE/ACM/AAAI/AAAS Fellow, member of the Academia Europaea)
Nanjing University, China
Prof. Ryuji Kohno (IEICE Life/IEEE Fellow)
Yokohama National University, Japan
Prof. Guoping Qiu
The University of Nottingham, UK & The University of Nottingham Ningbo, China
Invited Speakers:
Prof. Antonio Alarcón-Paredes
National Polytechnic Institute, Mexico
Prof. Abril Uriarte Arcia
CIDETEC - IPN, Mexico
Asst. Prof. Isaac Kofi Nti
University of Cincinnati, USA
Assoc. Prof. Jiaxin Cai
Xiamen University of Technology, China
Dr. Vishnu S. Pendyala
San Jose State University, USA
Topics:
Topics of interest for submission include, but are not limited to:
Track 1: Deep Learning and Neural Architectures
-Architectural Advances
-Efficient Training Techniques
Track 2: Reinforcement Learning and Sequential Decision Making
-Advanced Reinforcement Learning Algorithms
-Multi-Agent Reinforcement Learning
Track 3: Applied Machine Intelligence
-Machine Learning in Healthcare
-AI in Robotics
Track 4: Natural Language Processing and Multimodal Learning
-Large Language Models
-Multilingual and Low-Resource NLP
Track 5: Emerging Paradigms and Future Directions
-Quantum Machine Learning
-Federated and Distributed Learning
Track 6: Explainable, Ethical, and Human-Centered AI
-Explainable AI (XAI)
-Ethical AI and Fairness
Contact Us:
Conference Secretary: Miss Joie Wu
Email: mlmi_contact@163.com
Tel: +86-18302820449
Website: http://mlmi.net/
