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

4 – 6 Dec 2026·Japan

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  1. الرئيسية
  2. الفعاليات
  3. الذكاء الاصطناعي وتعلم الآلة والذكاء الاصطناعي التوليدي
  4. The 4th International Conference on Machine Learning and Pattern Recognition (MLPR 2026)
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Industry Events

المنصة العالمية الأكثر موثوقية لاكتشاف فعاليات B2B. نربط المهنيين في الصناعة بالمؤتمرات والمعارض والقمم المهمة.

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  • الأخبار
  • منظمو الفعاليات
  • من نحن
  • خدماتنا
  • منظم مميز
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  • كن متحدثاً
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  • الشروط
  • الخصوصية

© 2026 Industry Events Worldwide. جميع الحقوق محفوظة.

VF113.26.
Industry Events

المنصة العالمية الأكثر موثوقية لاكتشاف فعاليات B2B. نربط المهنيين في الصناعة بالمؤتمرات والمعارض والقمم المهمة.

  • فعاليات الصناعة
  • الأخبار
  • منظمو الفعاليات
  • من نحن
  • خدماتنا
  • منظم مميز
  • Event Pro
  • كن متحدثاً
  • اشتراك
  • الشروط
  • الخصوصية

© 2026 Industry Events Worldwide. جميع الحقوق محفوظة.

VF113.26.
الذكاء الاصطناعي وتعلم الآلة والذكاء الاصطناعي التوليدي

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

MLPR 2026

  • التاريخ

    4 - 6 December 2026

  • الموقع

    Kyoto, Japan

  • نوع الفعالية

    المؤتمرات والقمم

  • طريقة التقديم

    هجين (حضوري وعبر الإنترنت)

سجّل للحضور
شعار The 4th International Conference on Machine Learning and Pattern Recognition (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

1. 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.

2. 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

التسعير والتسجيل

رسوم الحضور

$100-500

USD لكل حضور

سجّل للحضور

التسعير والتسجيل

رسوم الحضور

$100-500

USD لكل حضور

سجّل للحضور

ابقَ على تواصل مع الفعالية

تابع الفعالية للاطلاع على التحديثات والإعلانات

زيارة موقع الفعالية

Sponsors & Partners

We're proud to partner with industry leaders supporting this event.

شريك إعلامي

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    IConf

الموقع وقاعة الفعالية

انضم إلينا في هذا المكان العالمي المصمم لإلهام التواصل المثمر.

الموقع

Kyoto, Japan

Kyoto, Japan

التاريخ والوقت

4 - 6 December 2026

المنطقة الزمن��ة

GMT+9 (Tokyo)

احصل على الاتجاهات
IA

تنظيم

International Association of Computer Science & Information Technology

Corporate

مشاركة:

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