{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,27]],"date-time":"2026-04-27T11:54:33Z","timestamp":1777290873485,"version":"3.51.4"},"publisher-location":"Cham","reference-count":18,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783319930398","type":"print"},{"value":"9783319930404","type":"electronic"}],"license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018]]},"DOI":"10.1007\/978-3-319-93040-4_21","type":"book-chapter","created":{"date-parts":[[2018,6,16]],"date-time":"2018-06-16T13:29:41Z","timestamp":1529155781000},"page":"260-272","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":196,"title":["MIDA: Multiple Imputation Using Denoising Autoencoders"],"prefix":"10.1007","author":[{"given":"Lovedeep","family":"Gondara","sequence":"first","affiliation":[]},{"given":"Ke","family":"Wang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2018,6,17]]},"reference":[{"key":"21_CR1","doi-asserted-by":"crossref","unstructured":"Beaulieu-Jones, B.K., Moore, J.H.: The pooled resource open-access ALS, and clinical trials consortium. Missing data imputation in the electronic health record using deeply learned autoencoders. In: Pacific Symposium on Biocomputing, vol. 22, pp. 207. NIH Public Access (2016)","DOI":"10.1142\/9789813207813_0021"},{"key":"21_CR2","unstructured":"Bengio, Y., Yao, L., Alain, G., Vincent, P.: Generalized denoising auto-encoders as generative models. In: Advances in Neural Information Processing Systems, pp. 899\u2013907 (2013)"},{"issue":"3","key":"21_CR3","doi-asserted-by":"publisher","first-page":"1","DOI":"10.18637\/jss.v045.i03","volume":"45","author":"S Buuren","year":"2011","unstructured":"Buuren, S., Groothuis-Oudshoorn, K.: MICE: multivariate imputation by chained equations in R. J. Stat. Softw. 45(3), 1\u201368 (2011)","journal-title":"J. Stat. Softw."},{"issue":"1","key":"21_CR4","doi-asserted-by":"publisher","first-page":"125","DOI":"10.1007\/s11263-008-0135-7","volume":"80","author":"P Chen","year":"2008","unstructured":"Chen, P.: Optimization algorithms on subspaces: revisiting missing data problem in low-rank matrix. Int. J. Comput. Vis. 80(1), 125\u2013142 (2008)","journal-title":"Int. J. Comput. Vis."},{"key":"21_CR5","doi-asserted-by":"crossref","unstructured":"Duan, Y., Lv, Y., Kang, W., Zhao, Y.: A deep learning based approach for traffic data imputation. In: 2014 IEEE 17th International Conference on Intelligent Transportation Systems (ITSC), pp. 912\u2013917. IEEE (2014)","DOI":"10.1109\/ITSC.2014.6957805"},{"issue":"7553","key":"21_CR6","doi-asserted-by":"publisher","first-page":"436","DOI":"10.1038\/nature14539","volume":"521","author":"Y LeCun","year":"2015","unstructured":"LeCun, Y., Bengio, Y., Hinton, G.: Deep learning. Nature 521(7553), 436\u2013444 (2015)","journal-title":"Nature"},{"key":"21_CR7","unstructured":"Leisch, F., Dimitriadou, E.: Machine learning benchmark problems (2010)"},{"key":"21_CR8","doi-asserted-by":"crossref","unstructured":"Li, S., Kawale, J., Fu, Y.: Deep collaborative filtering via marginalized denoising auto-encoder. In: Proceedings of the 24th ACM International on Conference on Information and Knowledge Management, pp. 811\u2013820. ACM (2015)","DOI":"10.1145\/2806416.2806527"},{"issue":"3","key":"21_CR9","doi-asserted-by":"crossref","first-page":"287","DOI":"10.1080\/07350015.1988.10509663","volume":"6","author":"RJA Little","year":"1988","unstructured":"Little, R.J.A.: Missing-data adjustments in large surveys. J. Bus. Econ. Stat. 6(3), 287\u2013296 (1988)","journal-title":"J. Bus. Econ. Stat."},{"key":"21_CR10","volume-title":"Statistical Analysis with Missing Data","author":"RJA Little","year":"2014","unstructured":"Little, R.J.A., Rubin, D.B.: Statistical Analysis with Missing Data. Wiley, Hoboken (2014)"},{"issue":"1","key":"21_CR11","doi-asserted-by":"publisher","first-page":"75","DOI":"10.1186\/1471-2288-14-75","volume":"14","author":"TP Morris","year":"2014","unstructured":"Morris, T.P., White, I.R., Royston, P.: Tuning multiple imputation by predictive mean matching and local residual draws. BMC Med. Res. Methodol. 14(1), 75 (2014)","journal-title":"BMC Med. Res. Methodol."},{"key":"21_CR12","unstructured":"Nelwamondo, F.V., Mohamed, S., Marwala, T.: Missing data: A comparison of neural network and expectation maximisation techniques. arXiv preprint arXiv:0704.3474 (2007)"},{"key":"21_CR13","unstructured":"Nesterov, Y.: A method of solving a convex programming problem with convergence rate O (1\/k2) (1983)"},{"key":"21_CR14","doi-asserted-by":"publisher","first-page":"581","DOI":"10.1093\/biomet\/63.3.581","volume":"63","author":"DB Rubin","year":"1976","unstructured":"Rubin, D.B.: Inference and missing data. Biometrika 63, 581\u2013592 (1976)","journal-title":"Biometrika"},{"issue":"1","key":"21_CR15","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1177\/096228029900800102","volume":"8","author":"JL Schafer","year":"1999","unstructured":"Schafer, J.L.: Multiple imputation: a primer. Stat. Methods Med. Res. 8(1), 3\u201315 (1999)","journal-title":"Stat. Methods Med. Res."},{"issue":"6","key":"21_CR16","doi-asserted-by":"publisher","first-page":"764","DOI":"10.1093\/aje\/kwt312","volume":"179","author":"AD Shah","year":"2014","unstructured":"Shah, A.D., Bartlett, J.W., Carpenter, J., Nicholas, O., Hemingway, H.: Comparison of random forest and parametric imputation models for imputing missing data using MICE: a CALIBER study. Am. J. Epidemiol. 179(6), 764\u2013774 (2014)","journal-title":"Am. J. Epidemiol."},{"key":"21_CR17","doi-asserted-by":"publisher","first-page":"b2393","DOI":"10.1136\/bmj.b2393","volume":"338","author":"JAC Sterne","year":"2009","unstructured":"Sterne, J.A.C., White, I.R., Carlin, J.B., Spratt, M., Royston, P., Kenward, M.G., Wood, A.M., Carpenter, J.R.: Multiple imputation for missing data in epidemiological and clinical research: potential and pitfalls. BMJ 338, b2393 (2009)","journal-title":"BMJ"},{"key":"21_CR18","doi-asserted-by":"crossref","unstructured":"Vincent, P., Larochelle, H., Bengio, Y., Manzagol, P.-A.: Extracting and composing robust features with denoising autoencoders. In: Proceedings of the 25th International Conference on Machine Learning, pp. 1096\u20131103. ACM (2008)","DOI":"10.1145\/1390156.1390294"}],"container-title":["Lecture Notes in Computer Science","Advances in Knowledge Discovery and Data Mining"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-93040-4_21","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,5]],"date-time":"2025-07-05T04:38:52Z","timestamp":1751690332000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-319-93040-4_21"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9783319930398","9783319930404"],"references-count":18,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-93040-4_21","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018]]},"assertion":[{"value":"17 June 2018","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"PAKDD","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Pacific-Asia Conference on Knowledge Discovery and Data Mining","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Melbourne, VIC","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Australia","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2018","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"3 June 2018","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"6 June 2018","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"pakdd2018","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/prada-research.net\/pakdd18\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}