Online Graph-Adaptive Learning With Scalability and Privacy

Volume: 67, Issue: 9, Pages: 2471 - 2483
Published: May 1, 2019
Abstract
Graphs are widely adopted for modeling complex systems, including financial, biological, and social networks. Nodes in networks usually entail attributes, such as the age or gender of users in a social network. However, real-world networks can have very large size, and nodal attributes can be unavailable to a number of nodes, e.g., due to privacy concerns. Moreover, new nodes can emerge over time, which can necessitate real-time evaluation of...
Paper Details
Title
Online Graph-Adaptive Learning With Scalability and Privacy
Published Date
May 1, 2019
Volume
67
Issue
9
Pages
2471 - 2483
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