{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/practical-methods-for-graph-two-sample","title":"Practical methods for graph two-sample testing","arxiv_id":"1811.12752","date":"2018-11-30","proceeding":"NeurIPS 2018 12","authors":["Debarghya Ghoshdastidar","Ulrike Von Luxburg"],"abstract":"Hypothesis testing for graphs has been an important tool in applied research\nfields for more than two decades, and still remains a challenging problem as\none often needs to draw inference from few replicates of large graphs. Recent\nstudies in statistics and learning theory have provided some theoretical\ninsights about such high-dimensional graph testing problems, but the\npracticality of the developed theoretical methods remains an open question.\n  In this paper, we consider the problem of two-sample testing of large graphs.\nWe demonstrate the practical merits and limitations of existing theoretical\ntests and their bootstrapped variants. We also propose two new tests based on\nasymptotic distributions. We show that these tests are computationally less\nexpensive and, in some cases, more reliable than the existing methods.","url_abs":"http://arxiv.org/abs/1811.12752v1","url_pdf":"http://arxiv.org/pdf/1811.12752v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"practical-methods-for-graph-two-sample","repo_url":"https://github.com/gdebarghya/Network-TwoSampleTesting","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":{"status":"ok"}}],"tasks":[{"task_slug":"learning-theory","task_name":"Learning Theory"},{"task_slug":"open-question","task_name":"Open-Ended Question Answering"},{"task_slug":"hypothesis-testing","task_name":"Two-sample testing"},{"task_slug":"two","task_name":"Vocal Bursts Valence Prediction"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1811.12752","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}