Study shows widely used machine learning methods don’t work as claimed

EurekAlert  March 16, 2020 A widely used algorithmic technique for modeling complex networks is to construct a low-dimensional Euclidean embedding of the vertices of the network, where proximity of vertices is interpreted as the likelihood of an edge. A team of researchers in the US (UC Santa Cruz, Google, Stanford University) focused on low degree and large clustering coefficients, which have been widely established to be empirically true for real-world networks. They demonstrated mathematically that significant structural aspects of complex networks are lost in this embedding process and confirmed this result empirically by testing various embedding techniques on different kinds […]