{"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/maximum-margin-interval-trees","title":"Maximum Margin Interval Trees","arxiv_id":"1710.04234","date":"2017-10-11","proceeding":"NeurIPS 2017 12","authors":["Alexandre Drouin","Toby Dylan Hocking","François Laviolette"],"abstract":"Learning a regression function using censored or interval-valued output data\nis an important problem in fields such as genomics and medicine. The goal is to\nlearn a real-valued prediction function, and the training output labels\nindicate an interval of possible values. Whereas most existing algorithms for\nthis task are linear models, in this paper we investigate learning nonlinear\ntree models. We propose to learn a tree by minimizing a margin-based\ndiscriminative objective function, and we provide a dynamic programming\nalgorithm for computing the optimal solution in log-linear time. We show\nempirically that this algorithm achieves state-of-the-art speed and prediction\naccuracy in a benchmark of several data sets.","url_abs":"http://arxiv.org/abs/1710.04234v2","url_pdf":"http://arxiv.org/pdf/1710.04234v2.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":"maximum-margin-interval-trees","repo_url":"https://github.com/aldro61/mmit","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":{"status":"ok","spdx":"GPL-3.0"}},{"paper_slug":"maximum-margin-interval-trees","repo_url":"https://github.com/lamtung16/ML_Changepoint_Detection_epigenomic_rnn","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok"}}],"tasks":[{"task_slug":"regression-1","task_name":"regression"}],"methods":[{"method_slug":"speed","method_name":"SPEED"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1710.04234","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}