Practical methods for graph two-sample testing

NeurIPS 2018 Debarghya GhoshdastidarUlrike von Luxburg

Hypothesis testing for graphs has been an important tool in applied research fields for more than two decades, and still remains a challenging problem as one often needs to draw inference from few replicates of large graphs. Recent studies in statistics and learning theory have provided some theoretical insights about such high-dimensional graph testing problems, but the practicality of the developed theoretical methods remains an open question... (read more)

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