{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,10]],"date-time":"2026-04-10T17:28:49Z","timestamp":1775842129184,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":21,"publisher":"ACM","license":[{"start":{"date-parts":[[2021,6,15]],"date-time":"2021-06-15T00:00:00Z","timestamp":1623715200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/100000001","name":"NSF (National Science Foundation)","doi-asserted-by":"publisher","award":["CCF-1704417,AF-1813049"],"award-info":[{"award-number":["CCF-1704417,AF-1813049"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000006","name":"Office of Naval Research","doi-asserted-by":"publisher","award":["N00014-18-1-2295"],"award-info":[{"award-number":["N00014-18-1-2295"]}],"id":[{"id":"10.13039\/100000006","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000015","name":"DOE U.S. Department of Energy","doi-asserted-by":"publisher","award":["DE-SC0019205"],"award-info":[{"award-number":["DE-SC0019205"]}],"id":[{"id":"10.13039\/100000015","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2021,6,15]]},"DOI":"10.1145\/3406325.3451050","type":"proceedings-article","created":{"date-parts":[[2021,6,16]],"date-time":"2021-06-16T01:26:13Z","timestamp":1623806773000},"page":"456-466","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":6,"title":["Stronger calibration lower bounds via sidestepping"],"prefix":"10.1145","author":[{"given":"Mingda","family":"Qiao","sequence":"first","affiliation":[{"name":"Stanford University, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gregory","family":"Valiant","sequence":"additional","affiliation":[{"name":"Stanford University, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2021,6,15]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1175\/1520-0493(1950)078<0001:VOFEIT>2.0.CO;2"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.1982.10477856"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1006\/game.1999.0719"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"crossref","unstructured":"Dean P Foster and Sergiu Hart. 2020. Forecast-Hedging and Calibration. http:\/\/www.ma.huji.ac.il\/hart\/papers\/calib-int.pdf. Accessed: 2020-12-01.","DOI":"10.1086\/716559"},{"key":"e_1_3_2_1_5_1","volume-title":"Conference on Learning Theory (COLT). 293\u2013314","author":"Foster Dean P","year":"2011","unstructured":"Dean P Foster, Alexander Rakhlin, Karthik Sridharan, and Ambuj Tewari. 2011. Complexity-based approach to calibration with checking rules. In Conference on Learning Theory (COLT). 293\u2013314."},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/85.2.379"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1006\/game.1999.0726"},{"key":"e_1_3_2_1_8_1","volume-title":"On Calibration of Modern Neural Networks. In International Conference on Machine Learning (ICML). 1321\u20131330","author":"Guo Chuan","year":"2017","unstructured":"Chuan Guo, Geoff Pleiss, Yu Sun, and Kilian Q Weinberger. 2017. On Calibration of Modern Neural Networks. In International Conference on Machine Learning (ICML). 1321\u20131330."},{"key":"e_1_3_2_1_9_1","volume-title":"Calibrated Forecasts: The Minimax Proof","author":"Hart Sergiu","year":"2020","unstructured":"Sergiu Hart. 2020. Calibrated Forecasts: The Minimax Proof. http:\/\/www.ma.huji.ac.il\/hart\/papers\/calib-minmax.pdf. Accessed: 2020-12-01."},{"key":"e_1_3_2_1_10_1","volume-title":"International Conference on Machine Learning (ICML). 1939\u20131948","author":"Hebert-Johnson Ursula","year":"2018","unstructured":"Ursula Hebert-Johnson, Michael Kim, Omer Reingold, and Guy Rothblum. 2018. Calibration for the (computationally-identifiable) masses. In International Conference on Machine Learning (ICML). 1939\u20131948."},{"key":"e_1_3_2_1_11_1","volume-title":"Moment Multicalibration for Uncertainty Estimation. arXiv preprint arXiv:2008.08037","author":"Jung Christopher","year":"2020","unstructured":"Christopher Jung, Changhwa Lee, Mallesh M Pai, Aaron Roth, and Rakesh Vohra. 2020. Moment Multicalibration for Uncertainty Estimation. arXiv preprint arXiv:2008.08037 (2020)."},{"key":"e_1_3_2_1_12_1","volume-title":"Inherent Trade-Offs in the Fair Determination of Risk Scores. In Innovations in Theoretical Computer Science Conference (ITCS). 43:1\u201343:23","author":"Kleinberg Jon","year":"2017","unstructured":"Jon Kleinberg, Sendhil Mullainathan, and Manish Raghavan. 2017. Inherent Trade-Offs in the Fair Determination of Risk Scores. In Innovations in Theoretical Computer Science Conference (ITCS). 43:1\u201343:23."},{"key":"e_1_3_2_1_13_1","unstructured":"Volodymyr Kuleshov and Percy S Liang. 2015. Calibrated structured prediction. In Advances in Neural Information Processing Systems (NIPS). 3474\u20133482."},{"key":"e_1_3_2_1_14_1","unstructured":"Ananya Kumar Percy S Liang and Tengyu Ma. 2019. Verified uncertainty calibration. In Advances in Neural Information Processing Systems (NeurIPS). 3792\u20133803."},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1111\/1468-0262.00244"},{"key":"e_1_3_2_1_16_1","unstructured":"Geoff Pleiss Manish Raghavan Felix Wu Jon Kleinberg and Kilian Q Weinberger. 2017. On fairness and calibration. In Advances in Neural Information Processing Systems (NIPS). 5680\u20135689."},{"key":"e_1_3_2_1_17_1","volume-title":"Chiara Sabatti, and Emmanuel J Cand\\`es.","author":"Romano Yaniv","year":"2019","unstructured":"Yaniv Romano, Rina Foygel Barber, Chiara Sabatti, and Emmanuel J Cand\\`es. 2019. With Malice Towards None: Assessing Uncertainty via Equalized Coverage. arXiv preprint arXiv:1908.05428 (2019)."},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1287\/moor.28.1.141.14264"},{"key":"e_1_3_2_1_19_1","volume-title":"Sample Complexity of Uniform Convergence for Multicalibration. arXiv preprint arXiv:2005.01757","author":"Shabat Eliran","year":"2020","unstructured":"Eliran Shabat, Lee Cohen, and Yishay Mansour. 2020. Sample Complexity of Uniform Convergence for Multicalibration. arXiv preprint arXiv:2005.01757 (2020)."},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.tcs.2007.07.026"},{"key":"e_1_3_2_1_21_1","volume-title":"Individual Calibration with Randomized Forecasting. In International Conference on Machine Learning (ICML). 8366\u20138376","author":"Zhao Shengjia","year":"2020","unstructured":"Shengjia Zhao, Tengyu Ma, and Stefano Ermon. 2020. Individual Calibration with Randomized Forecasting. In International Conference on Machine Learning (ICML). 8366\u20138376."}],"event":{"name":"STOC '21: 53rd Annual ACM SIGACT Symposium on Theory of Computing","location":"Virtual Italy","acronym":"STOC '21","sponsor":["SIGACT ACM Special Interest Group on Algorithms and Computation Theory"]},"container-title":["Proceedings of the 53rd Annual ACM SIGACT Symposium on Theory of Computing"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3406325.3451050","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3406325.3451050","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3406325.3451050","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T22:01:44Z","timestamp":1750197704000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3406325.3451050"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,6,15]]},"references-count":21,"alternative-id":["10.1145\/3406325.3451050","10.1145\/3406325"],"URL":"https:\/\/doi.org\/10.1145\/3406325.3451050","relation":{},"subject":[],"published":{"date-parts":[[2021,6,15]]},"assertion":[{"value":"2021-06-15","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}