{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,28]],"date-time":"2025-03-28T10:10:03Z","timestamp":1743156603600,"version":"3.40.3"},"publisher-location":"Cham","reference-count":22,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030923099"},{"type":"electronic","value":"9783030923105"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021]]},"DOI":"10.1007\/978-3-030-92310-5_60","type":"book-chapter","created":{"date-parts":[[2021,12,6]],"date-time":"2021-12-06T14:04:20Z","timestamp":1638799460000},"page":"519-527","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["MeTGAN: Memory Efficient Tabular GAN for\u00a0High Cardinality Categorical Datasets"],"prefix":"10.1007","author":[{"given":"Shreyansh","family":"Singh","sequence":"first","affiliation":[]},{"given":"Kanishka","family":"Kayathwal","sequence":"additional","affiliation":[]},{"given":"Hardik","family":"Wadhwa","sequence":"additional","affiliation":[]},{"given":"Gaurav","family":"Dhama","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,12,2]]},"reference":[{"key":"60_CR1","unstructured":"Data to AI Lab, at MIT: Sdmetrics (2020). https:\/\/github.com\/sdv-dev\/SDMetrics"},{"key":"60_CR2","unstructured":"Choi, E., Biswal, S., Malin, B., Duke, J., Stewart, W.F., Sun, J.: Generating multi-label discrete patient records using generative adversarial networks. In: Proceedings of the 2nd Machine Learning for Healthcare Conference, vol. 68. PMLR (2017)"},{"key":"60_CR3","doi-asserted-by":"publisher","unstructured":"Cormode, G., Procopiuc, C., Srivastava, D., Shen, E., Yu, T.: Differentially private spatial decompositions. In: 2012 IEEE 28th International Conference on Data Engineering, pp. 20\u201331 (2012). https:\/\/doi.org\/10.1109\/ICDE.2012.16","DOI":"10.1109\/ICDE.2012.16"},{"key":"60_CR4","doi-asserted-by":"publisher","first-page":"114582","DOI":"10.1016\/j.eswa.2021.114582","volume":"174","author":"J Engelmann","year":"2021","unstructured":"Engelmann, J., Lessmann, S.: Conditional wasserstein GAN-based oversampling of tabular data for imbalanced learning. Expert Syst. Appl. 174, 114582 (2021). https:\/\/doi.org\/10.1016\/j.eswa.2021.114582","journal-title":"Expert Syst. Appl."},{"key":"60_CR5","unstructured":"Goodfellow, I.J., et al.: Generative adversarial networks (2014)"},{"key":"60_CR6","unstructured":"Gulrajani, I., Ahmed, F., Arjovsky, M., Dumoulin, V., Courville, A.: Improved training of wasserstein GANs. In: Proceedings of the 31st International Conference on Neural Information Processing Systems, NIPS 2017, pp. 5769\u20135779. Curran Associates Inc., Red Hook (2017)"},{"key":"60_CR7","unstructured":"Kohavi, R., Becker, B.: Adult data set, May 1996. https:\/\/bit.ly\/3v3VDIj"},{"key":"60_CR8","doi-asserted-by":"publisher","first-page":"324","DOI":"10.1109\/JSAIT.2020.2983071","volume":"1","author":"Z Lin","year":"2020","unstructured":"Lin, Z., Khetan, A., Fanti, G., Oh, S.: PacGAN: the power of two samples in generative adversarial networks. IEEE J. Sel. Areas Inf. Theory 1, 324\u2013335 (2020)","journal-title":"IEEE J. Sel. Areas Inf. Theory"},{"key":"60_CR9","unstructured":"Mottini, A., Lheritier, A., Acuna-Agost, R.: Airline passenger name record generation using generative adversarial networks. CoRR abs\/1807.06657 (2018)"},{"issue":"10","key":"60_CR10","doi-asserted-by":"publisher","first-page":"1071","DOI":"10.14778\/3231751.3231757","volume":"11","author":"N Park","year":"2018","unstructured":"Park, N., Mohammadi, M., Gorde, K., Jajodia, S., Park, H., Kim, Y.: Data synthesis based on generative adversarial networks. Proc. VLDB Endow. 11(10), 1071\u20131083 (2018). https:\/\/doi.org\/10.14778\/3231751.3231757","journal-title":"Proc. VLDB Endow."},{"key":"60_CR11","doi-asserted-by":"publisher","unstructured":"Patki, N., Wedge, R., Veeramachaneni, K.: The synthetic data vault, pp. 399\u2013410, October 2016. https:\/\/doi.org\/10.1109\/DSAA.2016.49","DOI":"10.1109\/DSAA.2016.49"},{"key":"60_CR12","doi-asserted-by":"crossref","unstructured":"Peng, Z., et al.: Shrinking bigfoot: reducing wav2vec 2.0 footprint (2021)","DOI":"10.18653\/v1\/2021.sustainlp-1.14"},{"key":"60_CR13","unstructured":"Radford, A., Metz, L., Chintala, S.: Unsupervised representation learning with deep convolutional generative adversarial networks (2016)"},{"key":"60_CR14","first-page":"441","volume":"21","author":"J Reiter","year":"2005","unstructured":"Reiter, J.: Using cart to generate partially synthetic, public use microdata. J. Off. Stat. 21, 441\u2013462 (2005)","journal-title":"J. Off. Stat."},{"key":"60_CR15","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"535","DOI":"10.1007\/978-3-319-23485-4_53","volume-title":"Progress in Artificial Intelligence","author":"K Fernandes","year":"2015","unstructured":"Fernandes, K., Vinagre, P., Cortez, P.: A proactive intelligent decision support system for predicting the popularity of online news. In: Pereira, F., Machado, P., Costa, E., Cardoso, A. (eds.) EPIA 2015. LNCS (LNAI), vol. 9273, pp. 535\u2013546. Springer, Cham (2015). https:\/\/doi.org\/10.1007\/978-3-319-23485-4_53"},{"key":"60_CR16","unstructured":"Sanh, V., Debut, L., Chaumond, J., Wolf, T.: DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter. ArXiv abs\/1910.01108 (2019)"},{"key":"60_CR17","unstructured":"Tan, M., Le, Q.V.: EfficientNetV2: smaller models and faster training (2021)"},{"key":"60_CR18","unstructured":"Toktogaraev, M.: Should this loan be approved or denied? https:\/\/bit.ly\/3AptJaW"},{"key":"60_CR19","unstructured":"Xu, L., Skoularidou, M., Cuesta-Infante, A., Veeramachaneni, K.: Modeling tabular data using conditional GAN. In: NIPS (2019)"},{"key":"60_CR20","unstructured":"Xu, L., Veeramachaneni, K.: Synthesizing tabular data using generative adversarial networks. arXiv preprint arXiv:1811.11264 (2018)"},{"issue":"4","key":"60_CR21","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3134428","volume":"42","author":"J Zhang","year":"2017","unstructured":"Zhang, J., Cormode, G., Procopiuc, C.M., Srivastava, D., Xiao, X.: PrivBayes: private data release via Bayesian networks. ACM Trans. Database Syst. 42(4), 1\u201341 (2017)","journal-title":"ACM Trans. Database Syst."},{"key":"60_CR22","unstructured":"Zhao, Z., Kunar, A., der Scheer, H.V., Birke, R., Chen, L.Y.: CTAB-GAN: effective table data synthesizing (2021)"}],"container-title":["Communications in Computer and Information Science","Neural Information Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-92310-5_60","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,6,21]],"date-time":"2022-06-21T08:12:17Z","timestamp":1655799137000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-92310-5_60"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9783030923099","9783030923105"],"references-count":22,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-92310-5_60","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"type":"print","value":"1865-0929"},{"type":"electronic","value":"1865-0937"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"2 December 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICONIP","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Neural Information Processing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Sanur, Bali","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Indonesia","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 December 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12 December 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"28","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"iconip2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/iconip2021.apnns.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"1093","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"226","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"177","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"21% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2.57","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"6","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Due to the COVID-19 pandemic the conference was held online.","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}