{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,3]],"date-time":"2025-07-03T15:14:54Z","timestamp":1751555694061,"version":"3.28.0"},"reference-count":24,"publisher":"IEEE","license":[{"start":{"date-parts":[[2023,6,4]],"date-time":"2023-06-04T00:00:00Z","timestamp":1685836800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,6,4]],"date-time":"2023-06-04T00:00:00Z","timestamp":1685836800000},"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":[[2023,6,4]]},"DOI":"10.1109\/icassp49357.2023.10096599","type":"proceedings-article","created":{"date-parts":[[2023,5,5]],"date-time":"2023-05-05T13:28:30Z","timestamp":1683293310000},"page":"1-5","source":"Crossref","is-referenced-by-count":2,"title":["Implicit Bayes Adaptation: A Collaborative Transport Approach"],"prefix":"10.1109","author":[{"given":"Bo","family":"Jiang","sequence":"first","affiliation":[{"name":"North Carolina State University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hamid","family":"Krim","sequence":"additional","affiliation":[{"name":"North Carolina State University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tianfu","family":"Wu","sequence":"additional","affiliation":[{"name":"North Carolina State University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Derya","family":"Cansever","sequence":"additional","affiliation":[{"name":"US Army Research Office"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"article-title":"Connecting dots–from local covariance to empirical intrinsic geometry and locally linear embedding","year":"2018","author":"malik","key":"ref13"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"journal-title":"Geodesic Distance Estimation with Spherelets","year":"2019","author":"li","key":"ref12"},{"article-title":"Fast ot for latent domain adaptation","year":"2022","author":"roheda","key":"ref23"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-009-5152-4"},{"journal-title":"Mean and principal curvature estimation from noisy point cloud data of manifolds embedded in rn","year":"2016","author":"soliman","key":"ref14"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1214\/aoms\/1177729694"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.3390\/math9020168"},{"key":"ref22","first-page":"9729","article-title":"Momentum contrast for unsupervised visual representation learning","author":"he","year":"2020","journal-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2014.2347059"},{"key":"ref21","article-title":"Sinkhorn distances: Lightspeed computation of optimal transport","volume":"26","author":"cuturi","year":"2013","journal-title":"Advances in neural information processing systems"},{"key":"ref2","first-page":"97","article-title":"Learning transferable features with deep adaptation networks","author":"long","year":"2015","journal-title":"International Conference on Machine Learning"},{"article-title":"Refining selfsupervised learning in imaging: Beyond linear metric","year":"2022","author":"jiang","key":"ref1"},{"key":"ref17","first-page":"643","article-title":"Manifolds and differential geometry","author":"lee","year":"2009","journal-title":"Topology"},{"key":"ref16","article-title":"Mémoire sur la théorie des déblais et des remblais","author":"monge","year":"1781","journal-title":"Histoire de l’Académie Royale des Sciences de Paris"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1112\/blms\/7.3.261"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1007\/BF01601813"},{"key":"ref8","first-page":"3186","article-title":"Unbalanced minibatch optimal transport; applications to domain adaptation","author":"fatras","year":"2021","journal-title":"International Conference on Machine Learning"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00445"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-71246-8_45"},{"key":"ref4","article-title":"Supervised representation learning: Transfer learning with deep autoencoders","author":"zhuang","year":"2015","journal-title":"Twenty-Fourth International Joint Conference on Artificial Intelligence"},{"key":"ref3","first-page":"443","article-title":"Deep coral: Correlation alignment for deep domain adaptation","author":"sun","year":"2016","journal-title":"European Conference on Computer Vision"},{"key":"ref6","first-page":"447","article-title":"Deepjdot: Deep joint distribution optimal transport for unsupervised domain adaptation","author":"damodaran","year":"2018","journal-title":"Proceedings of the European Conference on Computer Vision (ECCV)"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.316"}],"event":{"name":"ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","start":{"date-parts":[[2023,6,4]]},"location":"Rhodes Island, Greece","end":{"date-parts":[[2023,6,10]]}},"container-title":["ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/10094559\/10094560\/10096599.pdf?arnumber=10096599","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,11,20]],"date-time":"2023-11-20T14:03:41Z","timestamp":1700489021000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10096599\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,6,4]]},"references-count":24,"URL":"https:\/\/doi.org\/10.1109\/icassp49357.2023.10096599","relation":{},"subject":[],"published":{"date-parts":[[2023,6,4]]}}}