MLMI 2024 : ACM--2024 The 7th International Conference on Machine Learning and Machine Intelligence (MLMI 2024)

Full name: ACM--2024 The 7th International Conference on Machine Learning and Machine Intelligence (MLMI 2024)
Abbreviation: MLMI 2024
http://www.mlmi.net/


*The 7th International Conference on Machine Learning and Machine Intelligence (MLMI 2024)*
Osaka, Japan | August 2-4, 2024


The 7th International Conference on Machine Learning and Machine Intelligence (MLMI 2024) will be held in Osaka, Japan during August 2-4, 2024. MLMI 2024 is organized by Ritsumeikan University, Japan.

Insightful presentations, engaging discussions, vibrant networking – MLMI 2024 has it all. With leading academics on the scientific committee of the event, the program is guaranteed to address the most relevant topics in the field of machine learning and machine intelligence. It's an opportunity to source feedback on your research, to get published in conference proceedings, and to explore the beautiful city Osaka, Japan.


☑Publication
Accepted papers after proper registration and presentation will be published in the International Conferen ce Proceedings Series by ACM (ISBN: 979-8-4007-1783-3), which will be archived in the ACM Digital Library, and indexed by Ei Compendex, Scopus, etc. (*All the previous Conference Proceedings have been archived in ACM Digital Library and have been indexed by Ei Compendex & Scopus.)


☑Topics
Topics of interest for submission include, but are not limited to:

- Artificial Neural Networks
- Genetic Algorithms
- Association Rule Learning
- Inductive Logic Programming
- Automata, Logic and Games
- Intelligent Systems
- Bayesian Networks
- Lambda Calculus and Types
- Clustering
- Logic and Proof
- Commercial Software
- Machine Learning
- Commercial Software with Open-Source Editions
- Models of Computation
- Complex Systems
- Object-Oriented Programming
- Computational Complexity
- Open-Source Software
- Computational Learning Theory
- Pattern Recognition
- Computational Linguistics
- Reinforcement Learning
- Computer Animation
- Representation Learning
- Computer Science
- Similarity and Metric Learning
- Computer System
- Sparse Dictionary Learning
- Concurrent Algorithms and Data Structures
- Supervised Learning
- Data Mining
- Support Vector Machines
- Decision Tree Learning
- Unsupervised Learning
- Deep Learning

For more topics, please visit: http://www.mlmi.net/cfp.html


☑Submission Guideline
♢ English is the official language. Paper should be prepared in English.
♢ Abstract submission is for presentation only without publication.
♢ Full paper submission is for both presentation and publication. (No less than 8 pages)
♢ Submission Methods:
- By online submission system: http://confsys.iconf.org/submission/mlmi2024
- Or Submit to [email protected] as attachment
For more details, please visit: http://www.mlmi.net/submission.html


☑Ritsumeikan University, Japan
The history of Ritsumeikan dates back to 1869 when Prince Kinmochi Saionji, an eminent international statesman of modern Japan, founded “Ritsumeikan” as a private academy on the site of the Kyoto Imperial Place. Ritsumeikan University offers a wide range of courses in advanced studies at its Kinugasa Campus in Kyoto, Biwako-Kusatsu Campus (BKC) in Shiga, and Osaka Ibaraki Campus in Osaka (OIC). Today, Ritsumeikan has become one of the most prestigious private universities in Japan, consistently earning one of the highest rankings among Japanese private universities in the renowned QS world university rankings. With its distinct strength in international orientation, it has been selected as part of the ongoing Top Global University Project by the Ministry of Education, Culture, Sports, Science and Technology (MEXT) since 2014. Ritsumeikan University is also being highly appraised by society as the world-class educational institution which attracts many students both in Japan and overseas, consisting of 16 colleges and 22 graduate schools.


☑Contact Us
Conference Secretary: Miss Joie Wu
Email: [email protected]
Tel: +86-18302820449
Website: http://mlmi.net/
Office Hour: Monday-Friday, 9:30-18:00 (GMT+8)