{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,7]],"date-time":"2025-11-07T19:35:38Z","timestamp":1762544138058,"version":"3.28.0"},"reference-count":44,"publisher":"IEEE","license":[{"start":{"date-parts":[[2022,9,27]],"date-time":"2022-09-27T00:00:00Z","timestamp":1664236800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,9,27]],"date-time":"2022-09-27T00:00:00Z","timestamp":1664236800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,9,27]]},"DOI":"10.1109\/allerton49937.2022.9929425","type":"proceedings-article","created":{"date-parts":[[2022,11,4]],"date-time":"2022-11-04T21:34:30Z","timestamp":1667597670000},"page":"1-8","source":"Crossref","is-referenced-by-count":0,"title":["Classifying Incomplete Data with a Mixture of Subspace Experts"],"prefix":"10.1109","author":[{"given":"Ben A.","family":"Kizaric","sequence":"first","affiliation":[{"name":"University of Wisconsin-Madison,Department of Electrical and Computer Engineering"}]},{"given":"Daniel L.","family":"Pimentel-Alarcon","sequence":"additional","affiliation":[{"name":"Wisconsin Institute for Discovery, University of Wisconsin-Madison"}]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1007\/s10115-013-0706-y"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.2002.1005474"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01421"},{"key":"ref32","article-title":"Semi-supervised learning with ladder networks","volume":"28","author":"rasmus","year":"2015","journal-title":"Advances in neural information processing systems"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.26599\/BDMA.2018.9020008"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-662-44851-9_36"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btab322"},{"key":"ref36","article-title":"missForest: Nonparametric missing value imputation using random forest","author":"stekhoven","year":"2015","journal-title":"Astrophysics Source Code Library"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1201\/9781439821862"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.18637\/jss.v045.i04"},{"key":"ref10","first-page":"1","article-title":"Xgboost: extreme gradient boosting","volume":"1","author":"chen","year":"2015","journal-title":"R package version 0 4-2"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2012.2211477"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-019-05855-6"},{"journal-title":"UCI Machine Learning Repository","year":"2017","author":"dua","key":"ref12"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2013.57"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1186\/s40537-021-00516-9"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1007\/s11045-016-0393-4"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-009-0295-6"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2011.06.023"},{"key":"ref18","first-page":"169","article-title":"Multi-manifold semi-supervised learning","author":"goldberg","year":"2009","journal-title":"Artificial Intelligence and Statistics"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1007\/s00500-015-1623-7"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.3390\/e24040533"},{"key":"ref28","article-title":"Semi-supervised learning with generative adversarial networks","author":"odena","year":"2016","journal-title":"ArXiv Preprint"},{"key":"ref3","article-title":"Experimental comparison of K-nearest neighbor and mean or mode imputation methods with the internal strategies used by C4. 5 and CN2 to treat missing data","volume":"34","author":"batista","year":"2003","journal-title":"Universidade de Sao Paulo"},{"key":"ref27","doi-asserted-by":"crossref","first-page":"1921","DOI":"10.1109\/TIP.2010.2044958","article-title":"Flexible manifold embedding: A framework for semi-supervised and unsupervised dimension reduction","volume":"19","author":"nie","year":"2010","journal-title":"IEEE Transactions on Image Processing"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-21551-3_33"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1023\/A:1008324625522"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/SSP.2016.7551734"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1111\/rssb.12228"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1137\/080738970"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/SSP.2012.6319774"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-018-24271-9"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/ALLERTON.2010.5706976"},{"key":"ref20","article-title":"Semi-supervised Learning with Missing Values Imputation","author":"huang","year":"2021","journal-title":"ArXiv Preprint"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2017.2749574"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1991.3.1.79"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2004.10103"},{"key":"ref42","article-title":"Fashionmnist: a novel image dataset for benchmarking machine learning algorithms","author":"xiao","year":"2017","journal-title":"ArXiv Preprint"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1994.6.2.181"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2018.2872800"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2014.2332037"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00848"},{"key":"ref25","article-title":"Misgan: Learning from incomplete data with generative adversarial networks","author":"cheng-xian li","year":"2019","journal-title":"ArXiv Preprint"},{"key":"ref43","first-page":"5689","article-title":"Gain: Missing data imputation using generative adversarial nets","author":"yoon","year":"2018","journal-title":"International Conference on Machine Learning"}],"event":{"name":"2022 58th Annual Allerton Conference on Communication, Control, and Computing (Allerton)","start":{"date-parts":[[2022,9,27]]},"location":"Monticello, IL, USA","end":{"date-parts":[[2022,9,30]]}},"container-title":["2022 58th Annual Allerton Conference on Communication, Control, and Computing (Allerton)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9929313\/9929314\/09929425.pdf?arnumber=9929425","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,11,28]],"date-time":"2022-11-28T20:26:01Z","timestamp":1669667161000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9929425\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,9,27]]},"references-count":44,"URL":"https:\/\/doi.org\/10.1109\/allerton49937.2022.9929425","relation":{},"subject":[],"published":{"date-parts":[[2022,9,27]]}}}