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Federated Knowledge Graph Unlearning via Diffusion Model
March 14, 2024, 4:42 a.m. | Bingchen Liu, Yuanyuan Fang
cs.LG updates on arXiv.org arxiv.org
Abstract: Federated learning (FL) promotes the development and application of artificial intelligence technologies by enabling model sharing and collaboration while safeguarding data privacy. Knowledge graph (KG) embedding representation provides a foundation for knowledge reasoning and applications by mapping entities and relations into vector space. Federated KG embedding enables the utilization of knowledge from diverse client sources while safeguarding the privacy of local data. However, due to demands such as privacy protection and the need to adapt …
abstract application applications artificial artificial intelligence arxiv collaboration cs.ai cs.lg data data privacy development diffusion diffusion model embedding enabling federated learning foundation graph intelligence knowledge knowledge graph mapping privacy reasoning relations representation space technologies type unlearning vector via
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