Dynamic Fuzzy Lie Group Machine Learning: Advanced Theories and Practical Applications
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "E1: Mathematics and Computer Science".
Deadline for manuscript submissions: 31 March 2027 | Viewed by 61
Editors
Interests: lie group machine learning; cognitive software theory and methods; big data science and technology; artificial intelligence
Special Issues, Collections and Topics in MDPI journals
Interests: lie group machine learning; pattern recognition; data visualization
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Dynamic fuzzy Lie group machine learning is a novel paradigm of machine learning that deeply integrates dynamic fuzzy logic with Lie group machine learning. It aims to uniformly address the three core challenges commonly present in real-world data: dynamic nature, fuzziness and geometric structure. It breaks the bottleneck of traditional machine learning in handling dynamic, fuzzy and geometrically complex data, providing a new interpretable, robust and efficient path for artificial intelligence. It offers new methods for typical application scenarios such as 3D pose estimation, action recognition, image segmentation, face recognition, robotic arm control, simultaneous localization and mapping, multi-robot collaboration, healthcare, autonomous driving and industrial fault diagnosis. To enable those interested in researching and promoting dynamic fuzzy Lie group machine learning to have the opportunity to participate in this field of study, we are organizing the "Dynamic Fuzzy Lie Group Machine Learning: Advanced Theories and Practical Applications" conference. The main research contents include, but are not limited to, the following: dynamic fuzzy Lie group theory, dynamic fuzzy Lie group learnable theory, dynamic fuzzy Lie group machine learning interpretable theory, dynamic fuzzy Lie group continuous learning, dynamic fuzzy Lie group geometric learning, dynamic fuzzy Lie group network learning, dynamic fuzzy Lie group open learning, dynamic fuzzy Lie group multimodal fusion learning, dynamic fuzzy Lie group brain-inspired collaborative learning and dynamic fuzzy Lie group neural network learning.
Prof. Fanzhang Li
Dr. Li Liu
Guest Editors
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Keywords
- dynamic fuzzy lie group theory
- dynamic fuzzy lie group learnable theory
- dynamic fuzzy lie group machine learning interpretable theory
- dynamic fuzzy lie group continuous learning
- dynamic fuzzy lie group geometric learning
- dynamic fuzzy lie group network learning
- dynamic fuzzy lie group open learning
- dynamic fuzzy lie group multimodal fusion learning
- dynamic fuzzy lie group brain-like collaborative learning
- dynamic fuzzy lie group neural network learning
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