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On provable privacy vulnerabilities of graph representations
Graph representation learning (GRL) is critical for extracting insights from complex network structures, but it also raises security concerns due to potential privacy vulnerabilities in these representations.
Knowledge-inspired Subdomain Adaptation for Cross-Domain Knowledge Transfer
For example, consider cross-domain fraud detection, where there are two types of transactions: credit and non-credit.
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