Machine learning and deep methods have been employed in the hyperspectral image (HSI) classification field. Of methods, convolution neural network (CNN) has widely used achieved promising results. However, CNN its limitations modeling sample relations. Graph (GCN) introduced to HSI due demonstrated ability processing Introducing GCN into classification, key issue is how transform HSI, a typical...

We study the problem of detecting whether an inhomogeneous random graph contains a planted community. Specifically, we observe single realization graph. Under null hypothesis, this is sample from graph, whereas under alternative, there exists small subgraph where edge probabilities are increased by multiplicative scaling factor. present scan test that able to detect presence such community, eve...

Abstract Graph matching is a fruitful area in terms of both algorithms and theories. Given two graphs $$G_1 = (V_1, E_1)$$ G 1 = ( V , E ) $$G_2 ...