The 4th International Conference on Machine Learning and Pattern Recognition (MLPR 2026)

MLPR 2026


Engineering & Computer Science (General)



Full Name: The 4th International Conference on Machine Learning and Pattern Recognition (MLPR 2026)



Website: https://www.mlpr.org

Conference Date: December 4-6, 2026

Conference Venue: Kyoto, Japan



The 4th International Conference on Machine Learning and Pattern Recognition (MLPR 2026) will be held at Kyoto, Japan during December 4-6, 2026. MLPR 2026 is sponsored by Ritsumeikan University, Japan. The conference includes keynote talks, invited talks, forums and oral and poster presentations of author papers. We invite submissions of papers on all topics related to machine learning and pattern recognition for the main conference proceedings. All papers will be reviewed in a double-blind process and accepted papers will be presented at the conference. It is our pleasure to welcome you to MLPR 2026.



Committee

Conference Chairs

Yen-Wei Chen, Ritsumeikan University, Japan

Sam Kwong (IEEE Fellow), Lingnan University, Hong Kong, China



Conference Co-chair

Jianhua Zhang, Oslo Metropolitan University, Norway



Program Chairs

Raouf Hamzaoui, De Montfort University, UK

Chi-Man Pun, University of Macau, Macau, China

Edmund Lai, Auckland University of Technology, New Zealand

Hui Yuan, Shandong University, China

Tomoko Tateyama, University of the Ryukyus, Japan

Kezhi Mao, Nanyang Technological University, Singapore



Publication Chair

Yinhao Li, Ritsumeikan University, Japan



Publicity Chairs

T. Akilan, Lakehead University, Canada

Qingjie Meng, University of Birmingham, UK

Yutaro Iwamoto, Osaka Electro-Communication University, Japan

Yan Pang, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, China



Area Chair

Q. M. Jonathan Wu, University of Windsor, Canada



Local Organizing Chair

Jiaqing Liu, Ritsumeikan University, Japan



Keynote Speakers

Prof. Weisi Lin (IEEE/IET Fellow), Nanyang Technological University, Singapore

Prof. Sung-Bae Cho (IEEE/AAIA Fellow, Korean Academy of Science and Technology (KAST ), National Academy of Engineering of Korea (NAEK)), Yonsei University, South Korea

Prof. Cathal Gurrin, Dublin City University, Ireland



Publication

==Conference Proceedings==

Accepted papers of MLPR 2026 will be published in IET Conference Proceedings, which will be included in the IET Digital Library and IEEE Xplore and submitted to EI Compendex and Scopus for indexing.



==Journal Recommendation==

Selected registered paper can be recommended for potential publication in Intelligence & Robotics (ISSN: 2770-3541 (Online)).

Impact Factor:3.9(Q2)| CiteScore: 5.8

Indexing: SCI,Scopus,Google Scholar,CNKI

Note: The original price is $1,800; a 20% discount on the Article Processing Charge (APC) is available for full-paper submissions to the conference.



==Abstract Publication==

Accepted and registered abstracts of MLPR 2026 will be published in Intelligence & Robotics which will be submitted to SCI, Scopus, Google Scholar, CNKI for indexing free of charge.

Refer to the published linkage: https://www.oaepublish.com/articles/2574-1225.2025.154



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



Track 1: Foundations of Machine Learning

- Statistical learning theory and generalization bounds

- Optimization methods for deep learning (adaptive optimizers, loss landscapes)

- Dimensionality reduction and manifold learning

- Graphical models, causal inference, and probabilistic reasoning

- Active learning and query strategies

- Transfer, multi-task, and meta-learning

- Learning from noisy, limited, or imbalanced data

- Reinforcement learning theory and bandit algorithms



Track 2: Deep Learning & Generative Models

- Generative AI (diffusion models, VAEs, GANs, flow-based models)

- Large language models and vision-language models

- Transformer architectures and attention variants

- Self-supervised and foundation model pre-training

- Model compression (pruning, quantization, knowledge distillation)

- Neural architecture search and automated deep learning

- Graph neural networks and geometric deep learning

- Representation learning for video, 3D, and multimodal data



Track 3: Pattern Recognition & Computer Vision

- Feature extraction, selection, and descriptor learning

- Object detection, segmentation, and tracking

- Face, gesture, and action recognition

- Medical image analysis and computational pathology

- Remote sensing image analysis and Earth observation

- Document analysis and handwriting recognition

- Biometric recognition (fingerprint, iris, voice)

- 3D shape analysis and point cloud processing



Track 4: Responsible & Trustworthy AI

- Fairness, accountability, and transparency in ML models

- Explainable AI (XAI) and interpretability methods

- Robustness against adversarial attacks and out-of-distribution inputs

- Privacy-preserving ML (federated learning, differential privacy)

- AI safety, value alignment, and ethical frameworks

- Uncertainty quantification and reliable predictions

- Bias detection and mitigation in datasets and algorithms

- Regulatory compliance and auditable AI systems



Track 5: Applications of ML & Pattern Recognition

- ML for healthcare (diagnosis, drug discovery, genomics)

- Intelligent transportation and autonomous driving

- Natural language processing and speech recognition

- Recommender systems and personalization

- Time-series forecasting (finance, energy, IoT)

- Robotics and embodied AI

- Smart manufacturing and predictive maintenance

- Agriculture, environmental monitoring, and climate science



Track 6: Reinforcement Learning & Decision Intelligence

- Deep reinforcement learning algorithms (DQN, PPO, SAC, TD3)

- Multi-agent reinforcement learning and game-theoretic reasoning

- Inverse reinforcement learning and imitation learning

- Hierarchical reinforcement learning and option frameworks

- Offline reinforcement learning and batch RL

- Reinforcement learning from human feedback (RLHF)

- Sequential decision making under uncertainty (POMDPs, bandits)

- Applications of RL in robotics, autonomous driving, recommendation systems, and game AI



More Details please click: https://www.mlpr.org/cfp.html



Paper Requirement:

Papers should be prepared in English and carefully checked for correct grammar. Figures should be of high quality. Your submitted work must be original in the sense that it has never been published nor submitted for publication consideration anywhere. To ensure high scientific quality, all papers will be double-blind reviewed by the Technical Committee Members.



- Submission Types

* Both abstract and full paper submission can be presented and published. Full Paper should be no less than 5 full pages. If the paper length exceeds 6 printed pages, including all figures, tables, and references, extra page will be charged 60 USD per page.

- Submission Process

1) Download the Template for formatting your submission.

- Abstract Template: https://www.mlpr.org/files/template-abstract.docx

- Full Paper Template: https://www.mlpr.org/files/template.docx

2) Submit your paper to Online Submission System: http://confsys.iconf.org/submission/mlpr2026 or mlpr_Conf@outlook.com



More Details please click: https://www.mlpr.org/sub.html



Conference Program

Friday - December 4, 2026

  10:00 - 17:00    Sign In and Conference Material Collection

  16:00 - 18:00    Committee Conference

Saturday - December 5, 2026

  9:00 - 12:00     Opening Ceremony and Keynote Speeches

  12:00 - 13:30    Lunch

  13:30 - 15:30    Invited Speeches and Parallel Oral Sessions

  15:30 - 16:30    Poster Sessions

  16:30 - 18:30    Invited Speeches and Parallel Oral Sessions

  18:30 - 20:30    Dinner Banquet and Award Ceremony

Sunday - December 6, 2026

  9:00 - 12:00     Invited Speeches and Parallel Oral Sessions

  12:00 - 13:30    Lunch

  13:30 - 19:00    City Tour



Contact us

    Conference secretary: Miss Tessa Chen

    Tel: +86-13103333373

    Email: mlpr_Conf@outlook.com

    Office Hour: 9:30--18:00, Monday to Friday