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Sponsored AI Networking Cookbook: Practical recipes for AI-assisted network automation and development AI Networking Cookbook: Practical recipes for AI-assisted network automation and development

Author

Philip S. Yu

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Review Open access Jul 2026

Differentially Private Graph Learning: A Survey

This survey presents the first comprehensive and systematic review of Differentially Private Graph Learning (DPGL), and organizes existing DPGL methods into four categories based on the granularity of privacy protection, namely node-level, edge-level, graph-level, and node-level.

Li Sun, Long-Zhu He, Ming Li et al. · 1 citation
Jul 2026

Toward Personalized Differentially Private Learning for Decentralized Local Graphs

PPGNN, a personalized differentially private framework for decentralized graph data, enables user-specific privacy budgets during local perturbation while preserving analytical utility in decentralized graph learning scenarios.

Longzhu He, Peng Tang, Chaozhuo Li et al. · 0 citations

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