{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,30]],"date-time":"2026-01-30T23:39:39Z","timestamp":1769816379037,"version":"3.49.0"},"reference-count":40,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100000038","name":"Natural Sciences and Engineering Research Council of Canada","doi-asserted-by":"publisher","award":["CRDPJ 476594-14"],"award-info":[{"award-number":["CRDPJ 476594-14"]}],"id":[{"id":"10.13039\/501100000038","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000038","name":"Natural Sciences and Engineering Research Council of Canada","doi-asserted-by":"publisher","award":["RGPIN-2019-05019"],"award-info":[{"award-number":["RGPIN-2019-05019"]}],"id":[{"id":"10.13039\/501100000038","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000038","name":"Natural Sciences and Engineering Research Council of Canada","doi-asserted-by":"publisher","award":["RGPAS-2017-507965"],"award-info":[{"award-number":["RGPAS-2017-507965"]}],"id":[{"id":"10.13039\/501100000038","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Signal Process."],"published-print":{"date-parts":[[2020]]},"DOI":"10.1109\/tsp.2020.2979601","type":"journal-article","created":{"date-parts":[[2020,3,12]],"date-time":"2020-03-12T20:10:07Z","timestamp":1584043807000},"page":"1910-1922","source":"Crossref","is-referenced-by-count":12,"title":["Subsampling Generative Adversarial Networks: Density Ratio Estimation in Feature Space With Softplus Loss"],"prefix":"10.1109","volume":"68","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2183-607X","authenticated-orcid":false,"given":"Xin","family":"Ding","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3791-0249","authenticated-orcid":false,"given":"Z. Jane","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4575-3124","authenticated-orcid":false,"given":"William J.","family":"Welch","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref39","first-page":"2234","article-title":"Improved techniques for training GANs","author":"salimans","year":"0","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref38","article-title":"Unsupervised representation learning with deep convolutional generative adversarial networks","author":"radford","year":"2015"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1214\/aoms\/1177697731"},{"key":"ref31","article-title":"Some useful asymptotic theory","author":"shi","year":"0"},{"key":"ref30","article-title":"Generative adversarial nets from a density ratio estimation perspective","author":"uehara","year":"2016"},{"key":"ref37","doi-asserted-by":"crossref","first-page":"659","DOI":"10.1007\/978-0-387-73003-5_196","article-title":"Gaussian mixture models","volume":"741","author":"reynolds","year":"2009","journal-title":"Proc of Encyclopedia of Biometrics"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.425"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"key":"ref34","article-title":"Learning multiple layers of features from tiny images","author":"krizhevsky","year":"2009"},{"key":"ref10","first-page":"7354","article-title":"Self-attention generative adversarial networks","author":"zhang","year":"0","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref40","first-page":"6626","article-title":"GANs trained by a two time-scale update rule converge to a local Nash equilibrium","author":"heusel","year":"0","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref11","first-page":"214","article-title":"Wasserstein generative adversarial networks","volume":"70","author":"arjovsky","year":"0","journal-title":"Proc 34th Int Conf Mach Learn"},{"key":"ref12","first-page":"5767","article-title":"Improved training of Wasserstein GANs","author":"gulrajani","year":"0","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref13","volume":"338","author":"villani","year":"2008","journal-title":"Optimal Transport Old and New"},{"key":"ref14","first-page":"2203","article-title":"MMD GAN: Towards deeper understanding of moment matching network","author":"li","year":"0","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref15","first-page":"723","article-title":"A kernel two-sample test","volume":"13","author":"gretton","year":"2012","journal-title":"J Mach Learn Res"},{"key":"ref16","author":"azadi","year":"0","journal-title":"Proc Int Conf Learn Representations"},{"key":"ref17","first-page":"6345","article-title":"Metropolis-Hastings generative adversarial networks","volume":"97","author":"turner","year":"0","journal-title":"Proceedings 36th Int Conf Mach Learn"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1587\/transinf.2014EDP7335"},{"key":"ref19","article-title":"Deep density ratio estimation for change point detection","author":"khan","year":"2019"},{"key":"ref28","author":"mohri","year":"2012","journal-title":"Foundations of Machine Learning"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2019.2924554"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2014.2320500"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/LSP.2018.2890205"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2019.2894692"},{"key":"ref29","article-title":"Concentration of measure","author":"lafferty","year":"0"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2018.2820120"},{"key":"ref8","first-page":"659","article-title":"Large scale GAN training for high fidelity natural image synthesis","author":"brock","year":"2019","journal-title":"Proc Int Conf Learn Representations"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2919169"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2018.2836316"},{"key":"ref9","author":"miyato","year":"0","journal-title":"Proc Int Conf Learn Representations"},{"key":"ref1","first-page":"2672","article-title":"Generative adversarial nets","author":"goodfellow","year":"0","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref20","first-page":"11058","article-title":"Bias correction of learned generative models using likelihood-free importance weighting","author":"grover","year":"2019","journal-title":"Advances in Neural IInformation Processing Systems"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2005.849185"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4419-1576-4"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2011.2159500"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1016\/0041-5553(67)90040-7"},{"key":"ref26","author":"chakravarty","year":"1967","journal-title":"Handbook of Methods of Applied Statistics Volume I Techniques of Computation Descriptive Methods and Statistical Inference"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9781139035613"}],"container-title":["IEEE Transactions on Signal Processing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/78\/8933520\/09034113.pdf?arnumber=9034113","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,4,27]],"date-time":"2022-04-27T14:40:38Z","timestamp":1651070438000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9034113\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"references-count":40,"URL":"https:\/\/doi.org\/10.1109\/tsp.2020.2979601","relation":{},"ISSN":["1053-587X","1941-0476"],"issn-type":[{"value":"1053-587X","type":"print"},{"value":"1941-0476","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020]]}}}