{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,11]],"date-time":"2026-02-11T17:34:36Z","timestamp":1770831276456,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":55,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,11,14]],"date-time":"2024-11-14T00:00:00Z","timestamp":1731542400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,11,14]]},"DOI":"10.1145\/3677052.3698631","type":"proceedings-article","created":{"date-parts":[[2024,11,14]],"date-time":"2024-11-14T06:38:06Z","timestamp":1731566286000},"page":"45-53","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["Open Set Recognition for Random Forest"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6021-0243","authenticated-orcid":false,"given":"Guanchao","family":"Feng","sequence":"first","affiliation":[{"name":"BlackRock, Inc., United States"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-7728-0081","authenticated-orcid":false,"given":"Dhruv","family":"Desai","sequence":"additional","affiliation":[{"name":"BlackRock, Inc., United States"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-8005-3207","authenticated-orcid":false,"given":"Stefano","family":"Pasquali","sequence":"additional","affiliation":[{"name":"BlackRock, Inc., United States"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1040-9032","authenticated-orcid":false,"given":"Dhagash","family":"Mehta","sequence":"additional","affiliation":[{"name":"BlackRock, Inc., United States"}]}],"member":"320","published-online":{"date-parts":[[2024,11,14]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.mineng.2012.05.008"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/IV48863.2021.9575433"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298799"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jmva.2010.06.019"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11749-016-0481-7"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1023\/A:1010933404324"},{"key":"e_1_3_2_1_7_1","volume-title":"Classification and regression trees","author":"Breiman Leo","unstructured":"Leo Breiman. 2017. Classification and regression trees. Routledge."},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1023\/A:1010933404324"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/LSP.2022.3215917"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2024.3394660"},{"key":"e_1_3_2_1_11_1","volume-title":"Improving Open-Set Recognition with Bayesian Metric Learning. In ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 6185\u20136189","author":"Chen Tong","year":"2024","unstructured":"Tong Chen, Guanchao Feng, and Petar\u00a0M Djuri\u0107. 2024. Improving Open-Set Recognition with Bayesian Metric Learning. In ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 6185\u20136189."},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ygeno.2012.04.003"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1214\/23-AOAS1841"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/3604237.3626878"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1080\/21642583.2014.956265"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/N16-1061"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2021.3089459"},{"key":"e_1_3_2_1_18_1","first-page":"7068","article-title":"Exploring the limits of out-of-distribution detection","volume":"34","author":"Fort Stanislav","year":"2021","unstructured":"Stanislav Fort, Jie Ren, and Balaji Lakshminarayanan. 2021. Exploring the limits of out-of-distribution detection. Advances in Neural Information Processing Systems 34 (2021), 7068\u20137081.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_1_19_1","volume-title":"Why do tree-based models still outperform deep learning on typical tabular data?Advances in Neural Information Processing Systems 35","author":"Grinsztajn L\u00e9o","year":"2022","unstructured":"L\u00e9o Grinsztajn, Edouard Oyallon, and Ga\u00ebl Varoquaux. 2022. Why do tree-based models still outperform deep learning on typical tabular data?Advances in Neural Information Processing Systems 35 (2022), 507\u2013520."},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1145\/3533271.3561736"},{"key":"e_1_3_2_1_21_1","volume-title":"Methods of combining multiple classifiers and their applications to handwritten digit recognition. Unpublished master\u2019s thesis","author":"Kaynak C","year":"1995","unstructured":"C Kaynak. 1995. Methods of combining multiple classifiers and their applications to handwritten digit recognition. Unpublished master\u2019s thesis, Bogazici University (1995)."},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-33383-0"},{"key":"e_1_3_2_1_23_1","volume-title":"Lifelong learning","author":"Laal Marjan","year":"2012","unstructured":"Marjan Laal and Peyman Salamati. 2012. Lifelong learning; why do we need it?Procedia-Social and Behavioral Sciences 31 (2012), 399\u2013403."},{"key":"e_1_3_2_1_24_1","first-page":"358","article-title":"Classification and regression trees (CART)","volume":"40","author":"Li Bin","year":"1984","unstructured":"Bin Li, J Friedman, R Olshen, and C Stone. 1984. Classification and regression trees (CART). Biometrics 40, 3 (1984), 358\u2013361.","journal-title":"Biometrics"},{"key":"e_1_3_2_1_25_1","volume-title":"Quantile Regression using Random Forest Proximities. arXiv preprint arXiv:2408.02355","author":"Li Mingshu","year":"2024","unstructured":"Mingshu Li, Bhaskarjit Sarmah, Dhruv Desai, Joshua Rosaler, Snigdha Bhagat, Philip Sommer, and Dhagash Mehta. 2024. Quantile Regression using Random Forest Proximities. arXiv preprint arXiv:2408.02355 (2024)."},{"key":"e_1_3_2_1_26_1","volume-title":"Matthew Wiener","author":"Liaw Andy","year":"2002","unstructured":"Andy Liaw, Matthew Wiener, 2002. Classification and regression by randomForest. R news 2, 3 (2002), 18\u201322."},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1198\/016214505000001230"},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.5539\/ijef.v7n7p178"},{"key":"e_1_3_2_1_29_1","volume-title":"Quantitative risk management: Concepts, techniques and tools-revised edition","author":"McNeil J","unstructured":"Alexander\u00a0J McNeil, R\u00fcdiger Frey, and Paul Embrechts. 2015. Quantitative risk management: Concepts, techniques and tools-revised edition. Princeton University Press."},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-016-5610-8"},{"key":"e_1_3_2_1_31_1","unstructured":"Morningstar. 2018. \"Morningstar Categorization.\". https:\/\/www.morningstar.com\/content\/dam\/marketing\/shared\/research\/methodology\/860250-GlobalCategoryClassifications.pdf"},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01231-1_38"},{"key":"e_1_3_2_1_33_1","volume-title":"Anderson Rocha, and Ricardo Da\u00a0Silva Torres.","author":"Alberto\u00a0C\u00f3rdova Neira Manuel","year":"2018","unstructured":"Manuel Alberto\u00a0C\u00f3rdova Neira, Pedro Ribeiro\u00a0Mendes J\u00fanior, Anderson Rocha, and Ricardo Da\u00a0Silva Torres. 2018. Data-fusion techniques for open-set recognition problems. IEEE access 6 (2018), 21242\u201321265."},{"key":"e_1_3_2_1_34_1","volume-title":"A review of novelty detection. Signal processing 99","author":"Pimentel AF","year":"2014","unstructured":"Marco\u00a0AF Pimentel, David\u00a0A Clifton, Lei Clifton, and Lionel Tarassenko. 2014. A review of novelty detection. Signal processing 99 (2014), 215\u2013249."},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2022.3191696"},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2023.3263774"},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.17849\/insm-47-01-31-39.1"},{"key":"e_1_3_2_1_38_1","volume-title":"International Conference on Machine Learning. PMLR, 2152\u20132161","author":"Romera-Paredes Bernardino","year":"2015","unstructured":"Bernardino Romera-Paredes and Philip Torr. 2015. An embarrassingly simple approach to zero-shot learning. In International Conference on Machine Learning. PMLR, 2152\u20132161."},{"key":"e_1_3_2_1_39_1","volume-title":"Towards Enhanced Local Explainability of Random Forests: A Proximity-Based Approach. arXiv preprint arXiv:2310.12428","author":"Rosaler Joshua","year":"2023","unstructured":"Joshua Rosaler, Dhruv Desai, Bhaskarjit Sarmah, Dimitrios Vamvourellis, Deran Onay, Dhagash Mehta, and Stefano Pasquali. 2023. Towards Enhanced Local Explainability of Random Forests: A Proximity-Based Approach. arXiv preprint arXiv:2310.12428 (2023)."},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2012.256"},{"key":"e_1_3_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2016.2514489"},{"key":"e_1_3_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.1142\/S0129065704001899"},{"key":"e_1_3_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2021.11.011"},{"key":"e_1_3_2_1_44_1","doi-asserted-by":"publisher","DOI":"10.1080\/10618600.2022.2096621"},{"key":"e_1_3_2_1_45_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00131"},{"key":"e_1_3_2_1_46_1","doi-asserted-by":"crossref","unstructured":"Lisa Torrey and Jude Shavlik. 2010. Transfer learning. In Handbook of Research on Machine Learning Applications and Trends: Algorithms Methods and Techniques. IGI global 242\u2013264.","DOI":"10.4018\/978-1-60566-766-9.ch011"},{"key":"e_1_3_2_1_47_1","volume-title":"The variational Gaussian process. arXiv preprint arXiv:1511.06499","author":"Tran Dustin","year":"2015","unstructured":"Dustin Tran, Rajesh Ranganath, and David\u00a0M Blei. 2015. The variational Gaussian process. arXiv preprint arXiv:1511.06499 (2015)."},{"key":"e_1_3_2_1_48_1","doi-asserted-by":"publisher","DOI":"10.1109\/BTAS.2017.8272751"},{"key":"e_1_3_2_1_49_1","volume-title":"International Conference on Learning Representations.","author":"Vaze Sagar","year":"2022","unstructured":"Sagar Vaze, Kai Han, Andrea Vedaldi, and Andrew Zisserman. 2022. Open-Set Recognition: a Good Closed-Set Classifier is All You Need?. In International Conference on Learning Representations."},{"key":"e_1_3_2_1_50_1","doi-asserted-by":"publisher","DOI":"10.1109\/RADAR.2018.8557327"},{"key":"e_1_3_2_1_51_1","volume-title":"Generalizing from a few examples: A survey on few-shot learning. ACM Computing Surveys (csur) 53, 3","author":"Wang Yaqing","year":"2020","unstructured":"Yaqing Wang, Quanming Yao, James\u00a0T Kwok, and Lionel\u00a0M Ni. 2020. Generalizing from a few examples: A survey on few-shot learning. ACM Computing Surveys (csur) 53, 3 (2020), 1\u201334."},{"key":"e_1_3_2_1_52_1","volume-title":"Gaussian processes for machine learning. Vol.\u00a02","author":"Williams KI","unstructured":"Christopher\u00a0KI Williams and Carl\u00a0Edward Rasmussen. 2006. Gaussian processes for machine learning. Vol.\u00a02. MIT Press Cambridge, MA."},{"key":"e_1_3_2_1_53_1","doi-asserted-by":"publisher","DOI":"10.4018\/jdwm.2012040103"},{"key":"e_1_3_2_1_54_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-024-02117-4"},{"key":"e_1_3_2_1_55_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2018.07.030"}],"event":{"name":"ICAIF '24: 5th ACM International Conference on AI in Finance","location":"Brooklyn NY USA","acronym":"ICAIF '24"},"container-title":["Proceedings of the 5th ACM International Conference on AI in Finance"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3677052.3698631","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3677052.3698631","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T17:13:32Z","timestamp":1755882812000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3677052.3698631"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,11,14]]},"references-count":55,"alternative-id":["10.1145\/3677052.3698631","10.1145\/3677052"],"URL":"https:\/\/doi.org\/10.1145\/3677052.3698631","relation":{},"subject":[],"published":{"date-parts":[[2024,11,14]]},"assertion":[{"value":"2024-11-14","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}