{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,25]],"date-time":"2025-06-25T13:40:09Z","timestamp":1750858809215,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":22,"publisher":"ACM","content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,12,18]]},"DOI":"10.1145\/3703323.3703330","type":"proceedings-article","created":{"date-parts":[[2025,6,25]],"date-time":"2025-06-25T12:03:28Z","timestamp":1750853008000},"page":"44-51","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["ForeCal: Random Forest-based Calibration for DNNs"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-4501-7044","authenticated-orcid":false,"given":"Dhruv","family":"Nigam","sequence":"first","affiliation":[{"name":"Dream11, Mumbai, India"}]}],"member":"320","published-online":{"date-parts":[[2025,6,25]]},"reference":[{"key":"e_1_3_3_1_2_2","unstructured":"Selcuk Bayraci and Orkun Susuz. 2019. A Deep Neural Network (DNN) based classification model in application to loan default prediction. (10 2019)."},{"key":"e_1_3_3_1_3_2","doi-asserted-by":"publisher","unstructured":"Barry Becker and Ronny Kohavi. 1996. Adult. UCI Machine Learning Repository. DOI: 10.24432\/C5XW20.","DOI":"10.24432\/C5XW20"},{"key":"e_1_3_3_1_4_2","doi-asserted-by":"publisher","unstructured":"Alexey Borisov Julia Kiseleva Ilya Markov and M.\u00a0D. Rijke. 2018. Calibration: A Simple Way to Improve Click Models. Proceedings of the 27th ACM International Conference on Information and Knowledge Management null (2018) null. 10.1145\/3269206.3269260","DOI":"10.1145\/3269206.3269260"},{"key":"e_1_3_3_1_5_2","doi-asserted-by":"publisher","unstructured":"Leo Breiman. 2001. Random Forests. Machine Learning 45 1 (2001) 5\u201332. 10.1023\/A:1010933404324","DOI":"10.1023\/A:1010933404324"},{"key":"e_1_3_3_1_6_2","doi-asserted-by":"publisher","DOI":"10.1145\/1390156.1390169"},{"key":"e_1_3_3_1_7_2","doi-asserted-by":"publisher","DOI":"10.1145\/2783258.2788613"},{"key":"e_1_3_3_1_8_2","unstructured":"Chuan Guo Geoff Pleiss Yu Sun and Kilian\u00a0Q. Weinberger. 2017. On Calibration of Modern Neural Networks. (2017). https:\/\/www.semanticscholar.org\/paper\/d65ce2b8300541414bfe51d03906fca72e93523c"},{"key":"e_1_3_3_1_9_2","unstructured":"Archit Karandikar Nicholas Cain Dustin Tran Balaji Lakshminarayanan Jonathon Shlens Michael\u00a0C. Mozer and Becca Roelofs. 2021. Soft Calibration Objectives for Neural Networks. arxiv:2108.00106\u00a0[cs.LG]"},{"key":"e_1_3_3_1_10_2","series-title":"(NIPS \u201920)","volume-title":"Proceedings of the 34th International Conference on Neural Information Processing Systems","author":"Krishnan Ranganath","year":"2020","unstructured":"Ranganath Krishnan and Omesh Tickoo. 2020. Improving model calibration with accuracy versus uncertainty optimization. In Proceedings of the 34th International Conference on Neural Information Processing Systems(NIPS \u201920). Curran Associates Inc., Red Hook, NY, USA, Article 1531, 12\u00a0pages."},{"key":"e_1_3_3_1_11_2","volume-title":"Advances in Neural Information Processing Systems","author":"Kumar Ananya","year":"2019","unstructured":"Ananya Kumar, Percy\u00a0S Liang, and Tengyu Ma. 2019. Verified Uncertainty Calibration. In Advances in Neural Information Processing Systems , H.\u00a0Wallach, H.\u00a0Larochelle, A.\u00a0Beygelzimer, F.\u00a0d'Alch\u00e9-Buc, E.\u00a0Fox, and R.\u00a0Garnett (Eds.), Vol.\u00a032. Curran Associates, Inc.https:\/\/proceedings.neurips.cc\/paper_files\/paper\/2019\/file\/f8c0c968632845cd133308b1a494967f-Paper.pdf"},{"key":"e_1_3_3_1_12_2","series-title":"Proceedings of Machine Learning Research","first-page":"2805","volume-title":"Proceedings of the 35th International Conference on Machine Learning","volume":"80","author":"Kumar Aviral","year":"2018","unstructured":"Aviral Kumar, Sunita Sarawagi, and Ujjwal Jain. 2018. Trainable Calibration Measures for Neural Networks from Kernel Mean Embeddings. In Proceedings of the 35th International Conference on Machine Learning(Proceedings of Machine Learning Research, Vol.\u00a080), Jennifer Dy and Andreas Krause (Eds.). PMLR, 2805\u20132814. https:\/\/proceedings.mlr.press\/v80\/kumar18a.html"},{"key":"e_1_3_3_1_13_2","unstructured":"Rachel\u00a0Longjohn Markelle\u00a0Kelly and Kolby Nottingham. 2017. UCI Machine Learning Repository. http:\/\/archive.ics.uci.edu\/ml"},{"key":"e_1_3_3_1_14_2","doi-asserted-by":"publisher","unstructured":"Rita\u00a0P. Moro S. and P. Cortez. 2012. Bank Marketing. UCI Machine Learning Repository. DOI: 10.24432\/C5K306.","DOI":"10.24432\/C5K306"},{"key":"e_1_3_3_1_15_2","unstructured":"Jishnu Mukhoti Viveka Kulharia Amartya Sanyal S. Golodetz Philip H.\u00a0S. Torr and P. Dokania. 2020. Calibrating Deep Neural Networks using Focal Loss. ArXiv abs\/2002.09437 (2020) null. https:\/\/www.semanticscholar.org\/paper\/07d440f44f5f955afef3c32f2610c7a716c36f97"},{"key":"e_1_3_3_1_16_2","doi-asserted-by":"publisher","unstructured":"Mahdi\u00a0Pakdaman Naeini G. Cooper and M. Hauskrecht. 2015. Obtaining Well Calibrated Probabilities Using Bayesian Binning. Proceedings of the... AAAI Conference on Artificial Intelligence. AAAI Conference on Artificial Intelligence 2015 (2015) 2901\u20132907. 10.1609\/aaai.v29i1.9602","DOI":"10.1609\/aaai.v29i1.9602"},{"key":"e_1_3_3_1_17_2","doi-asserted-by":"publisher","unstructured":"Alexandru Niculescu-Mizil and R. Caruana. 2005. Predicting good probabilities with supervised learning. Proceedings of the 22nd international conference on Machine learning null (2005) null. 10.1145\/1102351.1102430","DOI":"10.1145\/1102351.1102430"},{"key":"e_1_3_3_1_18_2","unstructured":"J. Platt. 1999. Probabilistic Outputs for Support vector Machines and Comparisons to Regularized Likelihood Methods. (1999). https:\/\/www.semanticscholar.org\/paper\/42e5ed832d4310ce4378c44d05570439df28a393"},{"key":"e_1_3_3_1_19_2","series-title":"Proceedings of Machine Learning Research","first-page":"33833","volume-title":"Proceedings of the 40th International Conference on Machine Learning","volume":"202","author":"Tao Linwei","year":"2023","unstructured":"Linwei Tao, Minjing Dong, and Chang Xu. 2023. Dual Focal Loss for Calibration. In Proceedings of the 40th International Conference on Machine Learning(Proceedings of Machine Learning Research, Vol.\u00a0202), Andreas Krause, Emma Brunskill, Kyunghyun Cho, Barbara Engelhardt, Sivan Sabato, and Jonathan Scarlett (Eds.). PMLR, 33833\u201333849. https:\/\/proceedings.mlr.press\/v202\/tao23a.html"},{"key":"e_1_3_3_1_20_2","first-page":"11809","volume-title":"Advances in Neural Information Processing Systems","author":"Wang Deng-Bao","year":"2021","unstructured":"Deng-Bao Wang, Lei Feng, and Min-Ling Zhang. 2021. Rethinking Calibration of Deep Neural Networks: Do Not Be Afraid of Overconfidence. In Advances in Neural Information Processing Systems , M.\u00a0Ranzato, A.\u00a0Beygelzimer, Y.\u00a0Dauphin, P.S. Liang, and J.\u00a0Wortman Vaughan (Eds.), Vol.\u00a034. Curran Associates, Inc., 11809\u201311820. https:\/\/proceedings.neurips.cc\/paper_files\/paper\/2021\/file\/61f3a6dbc9120ea78ef75544826c814e-Paper.pdf"},{"key":"e_1_3_3_1_21_2","unstructured":"B. Zadrozny and C. Elkan. 2001. Obtaining calibrated probability estimates from decision trees and naive Bayesian classifiers. (2001). https:\/\/www.semanticscholar.org\/paper\/4f67a122ec3723f08ad5cbefecad119b432b3304"},{"key":"e_1_3_3_1_22_2","doi-asserted-by":"publisher","unstructured":"B. Zadrozny and C. Elkan. 2002. Transforming classifier scores into accurate multiclass probability estimates. Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining null (2002) null. 10.1145\/775047.775151","DOI":"10.1145\/775047.775151"},{"key":"e_1_3_3_1_23_2","doi-asserted-by":"publisher","DOI":"10.1145\/775047.775151"}],"event":{"name":"CODS-COMAD 2024: 8th International Conference on Data Science and Management of Data (12th ACM IKDD CODS and 30th COMAD)","location":"Jodhpur India","acronym":"CODS-COMAD Dec '24"},"container-title":["Proceedings of the 8th International Conference on Data Science and Management of Data (12th ACM IKDD CODS and 30th COMAD)"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3703323.3703330","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,25]],"date-time":"2025-06-25T13:05:57Z","timestamp":1750856757000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3703323.3703330"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12,18]]},"references-count":22,"alternative-id":["10.1145\/3703323.3703330","10.1145\/3703323"],"URL":"https:\/\/doi.org\/10.1145\/3703323.3703330","relation":{},"subject":[],"published":{"date-parts":[[2024,12,18]]},"assertion":[{"value":"2025-06-25","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}