{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,11,27]],"date-time":"2024-11-27T05:41:10Z","timestamp":1732686070511,"version":"3.28.2"},"reference-count":37,"publisher":"IEEE","license":[{"start":{"date-parts":[[2024,9,22]],"date-time":"2024-09-22T00:00:00Z","timestamp":1726963200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,9,22]],"date-time":"2024-09-22T00:00:00Z","timestamp":1726963200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/100000001","name":"NSF","doi-asserted-by":"publisher","award":["CCF-2106339"],"award-info":[{"award-number":["CCF-2106339"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000185","name":"DARPA","doi-asserted-by":"publisher","award":["HR0011-24-9-0427"],"award-info":[{"award-number":["HR0011-24-9-0427"]}],"id":[{"id":"10.13039\/100000185","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,9,22]]},"DOI":"10.1109\/mlsp58920.2024.10734802","type":"proceedings-article","created":{"date-parts":[[2024,11,4]],"date-time":"2024-11-04T18:31:55Z","timestamp":1730745115000},"page":"1-6","source":"Crossref","is-referenced-by-count":0,"title":["Distributionally Robust Domain Adaptation via Optimal Transport"],"prefix":"10.1109","author":[{"given":"Akram S.","family":"Awad","sequence":"first","affiliation":[{"name":"University of Central Florida,Department of Electrical and Computer Engineering,Orlando,FL,USA"}]},{"given":"Shuchin","family":"Aeron","sequence":"additional","affiliation":[{"name":"Tufts University,Department of Electrical and Computer Engineering,Medford,Massachusetts"}]},{"given":"George K.","family":"Atia","sequence":"additional","affiliation":[{"name":"University of Central Florida,Department of Electrical and Computer Engineering,Orlando,FL,USA"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4615-7566-5"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1287\/mnsc.1050.0451"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1287\/educ.2019.0198"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1007\/s10957-006-9084-x"},{"key":"ref5","article-title":"Distribution-ally robust optimization: A review","author":"Rahimian","year":"2019","journal-title":"arXiv preprint"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1287\/opre.51.4.543.16101"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1137\/060654803"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1287\/moor.2015.0776"},{"key":"ref9","article-title":"Distributionally robust optimization and generalization in kernel methods","volume":"32","author":"Staib","year":"2019","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref10","first-page":"280","article-title":"Kernel distributionally robust optimization: Gen-eralized duality theorem and stochastic approximation","volume-title":"In-ternational Conference on Artificial Intelligence and Statistics","author":"Zhu","year":"2021"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1007\/s10107-017-1172-1"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1287\/moor.2022.1275"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1287\/opre.1090.0741"},{"issue":"103","key":"ref14","first-page":"1","article-title":"Regularization via mass transportation","volume":"20","author":"Shafieezadeh-Abadeh","year":"2019","journal-title":"Journal of Machine Learning Research"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2013.368"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D16-1046"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D19-1433"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/MLSP55844.2023.10285908"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.316"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2013.274"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2016.2615921"},{"key":"ref22","article-title":"Joint distribution optimal transportation for domain adaptation","volume":"30","author":"Courty","year":"2017","journal-title":"Advances in Neural Information Processing Systems"},{"issue":"58\u201363","key":"ref23","first-page":"94","article-title":"Optimal transport for applied mathe-maticians","volume":"55","author":"Santambrogio","year":"2015","journal-title":"Birk\u00e4user; NY"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1561\/2200000073"},{"key":"ref25","article-title":"Robust classification under sample selection bias","volume":"27","author":"Liu","year":"2014","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref26","first-page":"1270","article-title":"Robust covariate shift regression","volume-title":"Artificial In-telligence and Statistics","author":"Chen","year":"2016"},{"key":"ref27","article-title":"Kernel robust bias-aware prediction under covariate shift","author":"Liu","year":"2017","journal-title":"arXiv preprint"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1016\/j.cam.2023.115369"},{"key":"ref29","first-page":"2208","article-title":"Deep transfer learning with joint adaptation net-works","volume-title":"International Conference on Machine Learning","author":"Long","year":"2017"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/MLSP55844.2023.10286010"},{"key":"ref31","first-page":"1781","article-title":"M\u00e9moire sur la th\u00e9orie des d\u00e9blais et des rem-blais","author":"Monge","journal-title":"Histoire de l\u2019Acad\u00e9mie Royale des Sciences de Paris"},{"issue":"4","key":"ref32","doi-asserted-by":"crossref","first-page":"1381","DOI":"10.1007\/s10958-006-0049-2","article-title":"On the translocation of masses","volume":"133","author":"Leonid","year":"2006","journal-title":"Jour-nal of Mathematical Sciences"},{"key":"ref33","first-page":"29736","article-title":"Rates of estimation of optimal transport maps using plug-in estimators via barycentric projections","volume":"34","author":"Deb","year":"2021","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref34","article-title":"Distributionally robust logistic regression","volume":"28","author":"Abadeh","year":"2015","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref35","article-title":"Towards deep learning models resistant to adversarial attacks","author":"Madry","year":"2017","journal-title":"arXiv preprint"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/34.291440"}],"event":{"name":"2024 IEEE 34th International Workshop on Machine Learning for Signal Processing (MLSP)","start":{"date-parts":[[2024,9,22]]},"location":"London, United Kingdom","end":{"date-parts":[[2024,9,25]]}},"container-title":["2024 IEEE 34th International Workshop on Machine Learning for Signal Processing (MLSP)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/10734669\/10734712\/10734802.pdf?arnumber=10734802","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,27]],"date-time":"2024-11-27T03:59:22Z","timestamp":1732679962000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10734802\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,9,22]]},"references-count":37,"URL":"https:\/\/doi.org\/10.1109\/mlsp58920.2024.10734802","relation":{},"subject":[],"published":{"date-parts":[[2024,9,22]]}}}