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stat.ML2017
Introduction to Tensor Decompositions and their Applications in Machine Learning
Stephan Rabanser, Oleksandr Shchur, Stephan Günnemann
Tensors are multidimensional arrays of numerical values and therefore generalize matrices to multiple dimensions. While tensors first emerged in the psychometrics community in the…
stat.ML2017★ 184 cited
Deep Gaussian Embedding of Graphs: Unsupervised Inductive Learning via Ranking
Aleksandar Bojchevski, Stephan Günnemann
Methods that learn representations of nodes in a graph play a critical role in network analysis since they enable many downstream learning tasks. We propose Graph2Gauss - an approa…