NeurIPS 2018poster58 citations
Practical Methods for Graph Two-Sample Testing
Debarghya Ghoshdastidar, Ulrike von Luxburg
Abstract
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.
BibTeX
@inproceedings{NEURIPS2018_dfa92d8f,
author = {Ghoshdastidar, Debarghya and von Luxburg, Ulrike},
booktitle = {Advances in Neural Information Processing Systems},
editor = {S. Bengio and H. Wallach and H. Larochelle and K. Grauman and N. Cesa-Bianchi and R. Garnett},
pages = {},
publisher = {Curran Associates, Inc.},
title = {Practical Methods for Graph Two-Sample Testing},
url = {https://proceedings.neurips.cc/paper_files/paper/2018/file/dfa92d8f817e5b08fcaafb50d03763cf-Paper.pdf},
volume = {31},
year = {2018}
}