==Conference Proceedings==
Submitted papers will be peer reviewed by conference committees, and accepted papers after proper registration and presentation will be published in the International Conference Proceedings Series by ACM, which will be submitted for indexing by Ei Compendex, Scopus, etc.

==Conference Committees==
Advisory Chair
Zhihua Zhou (IEEE/ACM/AAAI/AAAS Fellow, member of the Academia Europaea), Nanjing University, China

Conference Chairs
Yen-Wei Chen, Ritsumeikan University, Japan
James Tin-Yau Kwok (IEEE Fellow), Hong Kong University of Science and Technology, Hong Kong, China
Jianhua Zhang, Oslo Metropolitan University, Norway

Conference Co-chairs
Hiroyuki KUDO, Tsukuba University, Japan
Jianjun Li, Hangzhou Normal University, China

Program Chairs
Sung-Bae Cho, Yonsei University, South Korea
Jien Kato, Ritsumeikan University, Japan
Tomoko Tateyama, Fujita Health University, Japan
Xiaolin Qin, University of Chinese Academy of Sciences, China
Guoxian Yu, Shandong University, China
For more conference committees, please visit: https://www.mlpr.org/com.html

==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

==Call for Paper==
Track 1: Machine Learning
▪ Active learning
▪ Dimensionality reduction
▪ Feature selection
▪ Graphical models
▪ Imitation learning
▪ Intelligent Business Computing
▪ Intelligent Systems
▪ Intelligent control system
▪ Intelligent human machine interface
▪ Intelligent robot
▪ Latent variable models
▪ Learning for big data
▪ Learning from noisy supervision
▪ Learning in graphs
▪ Multi-objective learning
▪ Multiple instance learning
▪ Multi-task learning

Track 2: Pattern Recognition
▪ Analysis and detection of singularities
▪ Animation image analysis
▪ Classification
▪ Cluster analysis
▪ Deformation analysis
▪ Descriptor of shapes
▪ Diagnosis of faults
▪ Document analysis
▪ Emotion computation
▪ Enhancement and restoration
▪ Feature extraction
▪ Hand gestures classification
▪ Human face recognition
▪ Image compression
▪ Image fusion
▪ Image indexing and retrieval
▪ Image recovery
For more topics, please check: http://www.mlpr.org/cfp.html

Submission Requirements
1). Language
English is the official language of the conference; the paper should be written and presented only in English.
2). Submission Type
* Abstract submission for presentation only without publication.
* Full paper submission for both presentation and publication.
3). Paper Length
Full Paper should be no less than 8 full pages. Any manuscript of more than 10 pages will be charged for pages exceeding the limit.
4). Papers submitted to the conference should report original, previously unpublished research results, experiments or theories and must not be under consideration for publication elsewhere.

Submission Process
1). Download the Paper Template for formatting your paper.
2). Submit your paper to Online Submission System (http://confsys.iconf.org/submission/mlpr2025) or mlpr_Conf@outlook.com.
– via online submission system: an account is needed, if you don’t have, please register first.
– via mailbox: the email subject should be named as “Submission-MLPR 2025-Full Paper/ Abstract”
3). The conference secretary (mlpr_Conf@outlook.com) will contact you within three working days once receiving your submission.

==Contact==
The secretary of MLPR 2025 will collect your paper contributions and respond to your queries. If you have any questions, please feel free to contact the conference secretary.
Conference Secretary: Miss Luna Wu
Email: mlpr_Conf@outlook.com
Tel.: +86-18000547208
Office Hour: Mon. – Fri. 9:30-18:00 (GMT+8 Time Zone)