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Quaternion adaptive approximation normalization graph guided implicit low rank for robust matrix completion | Synapse
March 3, 2026
Quaternion adaptive approximation normalization graph guided implicit low rank for robust matrix completion
YG
Yu Guo
Sun Yat-sen University
YL
Yi Liu
Yangtze University
QJ
Qiyu Jin
Inner Mongolia University
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Key Points
Robust matrix completion techniques utilizing quaternion methods demonstrate significant performance enhancement.
Key improvements include up to a 25% increase in accuracy compared to conventional methods.
Analysis employs a graph-guided framework with implicit normalization strategies to refine outcomes.
These findings highlight the potential for advanced quaternion techniques, indicating a shift towards more effective matrix processing.
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Guo et al. (Sat,) studied this question.
synapsesocial.com/papers/69a75ea1c6e9836116a296cd
https://doi.org/https://doi.org/10.1016/j.patcog.2026.113210
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