{"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/discovering-reliable-dependencies-from-data","title":"Discovering Reliable Dependencies from Data: Hardness and Improved Algorithms","arxiv_id":"1809.05467","date":"2018-09-14","proceeding":null,"authors":["Panagiotis Mandros","Mario Boley","Jilles Vreeken"],"abstract":"The reliable fraction of information is an attractive score for quantifying\n(functional) dependencies in high-dimensional data. In this paper, we\nsystematically explore the algorithmic implications of using this measure for\noptimization. We show that the problem is NP-hard, which justifies the usage of\nworst-case exponential-time as well as heuristic search methods. We then\nsubstantially improve the practical performance for both optimization styles by\nderiving a novel admissible bounding function that has an unbounded potential\nfor additional pruning over the previously proposed one. Finally, we\nempirically investigate the approximation ratio of the greedy algorithm and\nshow that it produces highly competitive results in a fraction of time needed\nfor complete branch-and-bound style search.","url_abs":"http://arxiv.org/abs/1809.05467v1","url_pdf":"http://arxiv.org/pdf/1809.05467v1.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":"discovering-reliable-dependencies-from-data","repo_url":"https://github.com/pmandros/fodiscovery","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"heuristic-search","task_name":"Heuristic Search"}],"methods":[{"method_slug":"pruning","method_name":"Pruning"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}