首页|New Findings from China Jiliang University Update Understanding of Computational Intelligence (A Multi-view Graph Contrastive Learning Framework for Defending A gainst Adversarial Attacks)
New Findings from China Jiliang University Update Understanding of Computational Intelligence (A Multi-view Graph Contrastive Learning Framework for Defending A gainst Adversarial Attacks)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on Machine Learn ing - Computational Intelligence have been published. According to news reportin g from Hangzhou, People’s Republic of China, by NewsRx journalists, research sta ted, “Graph neural networks are easily deceived by adversarial attacks that inte ntionally modify the graph structure. Particularly, homophilous edges connecting similar nodes can be maliciously deleted when adversarial edges are inserted in to the graph.” Financial support for this research came from National Natural Science Foundatio n of China (NSFC).
HangzhouPeople’s Republic of ChinaAs iaComputational IntelligenceMachine LearningChina Jiliang University
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