{"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/robust-optimization-using-machine-learning","title":"Robust Optimization using Machine Learning for Uncertainty Sets","arxiv_id":"1407.1097","date":"2014-07-04","proceeding":null,"authors":["Theja Tulabandhula","Cynthia Rudin"],"abstract":"Our goal is to build robust optimization problems for making decisions based\non complex data from the past. In robust optimization (RO) generally, the goal\nis to create a policy for decision-making that is robust to our uncertainty\nabout the future. In particular, we want our policy to best handle the the\nworst possible situation that could arise, out of an uncertainty set of\npossible situations. Classically, the uncertainty set is simply chosen by the\nuser, or it might be estimated in overly simplistic ways with strong\nassumptions; whereas in this work, we learn the uncertainty set from data\ncollected in the past. The past data are drawn randomly from an (unknown)\npossibly complicated high-dimensional distribution. We propose a new\nuncertainty set design and show how tools from statistical learning theory can\nbe employed to provide probabilistic guarantees on the robustness of the\npolicy.","url_abs":"http://arxiv.org/abs/1407.1097v1","url_pdf":"http://arxiv.org/pdf/1407.1097v1.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":"robust-optimization-using-machine-learning","repo_url":"https://github.com/priyanka-sharma29/Robust-Optimization-using-Machine-Learning-for-building-Uncertainty-Sets","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok"}}],"tasks":[{"task_slug":"machine-learning","task_name":"BIG-bench Machine Learning"},{"task_slug":"decision-making","task_name":"Decision Making"},{"task_slug":"learning-theory","task_name":"Learning Theory"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":"https://app.syntology.ai/?focus=1407.1097","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}