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Coinciding Walk Kernels: Parallel Absorbing Random Walks for Learning with Graphs and Few Labels
2013
Asian Conference on Machine Learning
Exploiting autocorrelation for node-label prediction in networked data has led to great success. However, when dealing with sparsely labeled networks, common in present-day tasks, the autocorrelation assumption is difficult to exploit. Taking a step beyond, we propose the coinciding walk kernel (cwk), a novel kernel leveraging label-structure similarity -the idea that nodes with similarly arranged labels in their local neighbourhoods are likely to have the same label -for learning problems on
dblp:conf/acml/NeumannGK13
fatcat:k5w4ub2vife4zhogqhztge5onu