Conference Information
MLMC 2026: International Symposium on Machine Learning and Media Computing
http://itlab.fzu.edu.cn/MLMC2026/Submission Date: |
2026-03-20 |
Notification Date: |
2026-05-08 |
Conference Date: |
2026-07-30 |
Location: |
Nanping, China |
Years: |
2 |
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Call For Papers
The 2nd International Symposium on Machine Learning and Media Computing (MLMC 2026) is the flagship conference of the IEEE Systems, Man, and Cybernetics Society. It aims to provide an international forum for researchers and educators to learn, share knowledge, report most recent innovations and developments, and promote exchange of ideas and advances in all aspects of machine learning and media computing.
MLMC 2026 will be held in Nanping, Fujian, China, on July 30-31, 2026. The Symposium will showcase high quality oral presentations and special sessions sponsored by IEEE SMC and Fuzhou University. In MLMC 2026 exceptional papers and contributors will be selected and recognized with prestigious awards.
Journal Paper Presentation
Authors of papers published from 2024-2026 in all IEEE Systems, Man, and Cybernetics Society fully owned journals as well as in IEEE TPAMI, IEEE TIP, IEEE TMM, IEEE TCSVT, IEEE TIFS, IEEE TSP will be given the opportunity to present their works at MLMC 2026, subject to space availability and approval by the Technical Program Committee.
Topics of interest include (but not limited to)
Fundamental theories of machine learning
Classification / regression / clustering
Multi-modal/view/label/instance learning
Generalization and robustness of models
Heuristic optimization
Evolutionary computation
Efficient and lightweight model design
Trustworthy and/or explainable AI
Multimodal foundation models
Media representation and quality assessment
Media compression and delivery
Media restoration and enhancement
Media retrieval and recommendation
Media interpretation and understanding
Media security, privacy and forensics
Cross-modal generation and interaction
Internet of media things
Learning and media computing on embodied AI
Last updated by Dou Sun in 2025-11-27