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.




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.



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.
* Abstract submission for presentation only without publication.
* Full paper submission for both presentation and publication. 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 Method:
* Online Submission System: http://confsys.iconf.org/submission/mlpr2026.

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 (GMT+8 Time Zone)