{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T20:21:33Z","timestamp":1740169293652,"version":"3.37.3"},"reference-count":48,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"am","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000183","name":"Army Research Office","doi-asserted-by":"publisher","award":["W911NF-19-1-0269","W911NF-15-1-0479"],"award-info":[{"award-number":["W911NF-19-1-0269","W911NF-15-1-0479"]}],"id":[{"id":"10.13039\/100000183","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000015","name":"Department of Energy","doi-asserted-by":"publisher","award":["DE-NA0003921"],"award-info":[{"award-number":["DE-NA0003921"]}],"id":[{"id":"10.13039\/100000015","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2023]]},"DOI":"10.1109\/access.2023.3282932","type":"journal-article","created":{"date-parts":[[2023,6,5]],"date-time":"2023-06-05T17:56:26Z","timestamp":1685987786000},"page":"61513-61524","source":"Crossref","is-referenced-by-count":1,"title":["Any-Shot Learning From Multimodal Observations (ALMO)"],"prefix":"10.1109","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5669-7749","authenticated-orcid":false,"given":"Mehmet","family":"Aktukmak","sequence":"first","affiliation":[{"name":"Electrical and Computer Engineering Department, University of Michigan, Ann Arbor, MI, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2014-3060","authenticated-orcid":false,"given":"Yasin","family":"Yilmaz","sequence":"additional","affiliation":[{"name":"Electrical Engineering Department, University of South Florida, Tampa, FL, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2531-9670","authenticated-orcid":false,"given":"Alfred O.","family":"Hero","sequence":"additional","affiliation":[{"name":"Electrical and Computer Engineering Department, University of Michigan, Ann Arbor, MI, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref13","first-page":"5575","article-title":"Multimodal generative models for scalable weakly-supervised learning","author":"wu","year":"2018","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2022.3201203"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2021.3109375"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2021.107338"},{"key":"ref15","first-page":"15718","article-title":"Variational mixture-of-experts autoencoders for multi-modal deep generative models","author":"shi","year":"2019","journal-title":"Proc Adv Neural Inf Process Syst"},{"article-title":"Caltech-UCSD Birds 200","year":"0","author":"welinder","key":"ref37"},{"key":"ref14","article-title":"Generative models of visually grounded imagination","author":"vedantam","year":"2017","journal-title":"arXiv 1705 10762"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1162\/089976602760128018"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.557"},{"key":"ref30","first-page":"4790","article-title":"Conditional image generation with PixelCNN decoders","volume":"29","author":"van den oord","year":"2016","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref11","article-title":"Bayesian exponential family projections for coupled data sources","author":"klami","year":"2010","journal-title":"Proc 26th Conf Uncertainty Artif Intell"},{"key":"ref33","article-title":"Attribute prototype network for zero-shot learning","author":"xu","year":"2020","journal-title":"arXiv 2008 08290"},{"key":"ref10","first-page":"1230","article-title":"On the equivalence between canonical correlation analysis and orthonormalized partial least squares","volume":"9","author":"sun","year":"2009","journal-title":"Proc IJCAI"},{"key":"ref32","first-page":"14943","article-title":"Semantic-guided multi-attention localization for zero-shot learning","author":"zhu","year":"2019","journal-title":"Proc 33rd Adv Neural Inf Process Syst"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2013.140"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00581"},{"key":"ref17","first-page":"1","article-title":"Learning factorized multimodal representations","author":"tsai","year":"2019","journal-title":"Proc Int Conf Represent Learn"},{"key":"ref39","article-title":"Generating sequences with recurrent neural networks","author":"graves","year":"2013","journal-title":"arXiv 1308 0850 [cs]"},{"key":"ref16","article-title":"Deep variational canonical correlation analysis","author":"wang","year":"2016","journal-title":"arXiv 1610 03454"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.13"},{"key":"ref19","article-title":"Towards a neural statistician","author":"edwards","year":"2016","journal-title":"arXiv 1606 02185"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1145\/2993148.2993176"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/CRV52889.2021.00011"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.575"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/WACV48630.2021.00269"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00961"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.3390\/a15050147"},{"key":"ref48","article-title":"Auto-encoding variational Bayes","author":"kingma","year":"2013","journal-title":"arXiv 1312 6114"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-86340-1_39"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-71246-8_48"},{"key":"ref20","first-page":"7115","article-title":"TapNet: Neural network augmented with task-adaptive projection for few-shot learning","author":"yoon","year":"2019","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1016\/j.cobeha.2019.04.007"},{"key":"ref41","article-title":"Meta-learning probabilistic inference for prediction","author":"gordon","year":"2018","journal-title":"arXiv 1805 09921"},{"key":"ref22","first-page":"3630","article-title":"Matching networks for one shot learning","volume":"29","author":"vinyals","year":"2016","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00680"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.47"},{"key":"ref43","article-title":"A closer look at few-shot classification","author":"chen","year":"2019","journal-title":"arXiv 1904 04232"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00981"},{"key":"ref27","article-title":"The self-optimal-transport feature transform","author":"shalam","year":"2022","journal-title":"arXiv 2204 03065"},{"key":"ref29","article-title":"The variational homoencoder: Learning to learn high capacity generative models from few examples","author":"hewitt","year":"2018","journal-title":"arXiv 1807 08919"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1145\/1150402.1150454"},{"journal-title":"Machine Learning A Probabilistic Perspective","year":"2012","author":"murphy","key":"ref7"},{"key":"ref9","first-page":"733","article-title":"Bayesian factor regression models in the ‘large p, small n paradigm","volume":"7","author":"bernardo","year":"2003","journal-title":"Bayesian Statist"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/ICEIEC49280.2020.9152261"},{"key":"ref3","first-page":"2568","article-title":"One shot learning of simple visual concepts","volume":"33","author":"lake","year":"2011","journal-title":"Proc Annu Meeting Cogn Sci Soc"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.3390\/sym11091066"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1561\/2200000019"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2018.2857768"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"https:\/\/ieeexplore.ieee.org\/ielam\/6287639\/10005208\/10143628-aam.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/10005208\/10143628.pdf?arnumber=10143628","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,7,10]],"date-time":"2023-07-10T19:40:54Z","timestamp":1689018054000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10143628\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"references-count":48,"URL":"https:\/\/doi.org\/10.1109\/access.2023.3282932","relation":{},"ISSN":["2169-3536"],"issn-type":[{"type":"electronic","value":"2169-3536"}],"subject":[],"published":{"date-parts":[[2023]]}}}