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CSGO: Constrained-softassign gradient optimization for large graph matching
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DOI：10.1016/j.patcog.2026.113329.png)
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Abstract
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• A warm-start strategy. • Robustness to scaling and shifting changes on local information and global structure. • Automatic step size tuning that ensures algorithmic convergence while improving efficiency and accuracy. • A scalable softassign that scales well with increasing numbers of nodes.
Keywords:
warm-start strategy
robustness
automatic step size tuning
scalable softassign
graph matching
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7.6
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1.3W
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4.5W
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Graph matching for knowledge graph alignment using edge-coloring propagation.png)
PATTERN RECOGNITION
PATTERN RECOGNITIONIF7.6
PREAI
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Pattern RecognitionIF7.6
PREAI
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