MD Shafikul Islam
1 indexed paper
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126
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ML×1AI×1Crypto×1
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2026
Feature-Aware Anisotropic Local Differential Privacy for Utility-Preserving Graph Representation Learning in Metal Additive Manufacturing
The paper proposes FI-LDP-HGAT, a novel framework that combines a hierarchical graph attention network with feature-importance-aware anisotropic differential privacy to enable high-utility, privacy-preserving graph representation learning for metal additive manufacturing defect detection.
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