{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,13]],"date-time":"2026-02-13T14:52:27Z","timestamp":1770994347118,"version":"3.50.1"},"reference-count":67,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"9","license":[{"start":{"date-parts":[[2024,9,1]],"date-time":"2024-09-01T00:00:00Z","timestamp":1725148800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2024,9,1]],"date-time":"2024-09-01T00:00:00Z","timestamp":1725148800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,9,1]],"date-time":"2024-09-01T00:00:00Z","timestamp":1725148800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62206108"],"award-info":[{"award-number":["62206108"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"A*STAR Centre for Frontier AI Research"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Neural Netw. Learning Syst."],"published-print":{"date-parts":[[2024,9]]},"DOI":"10.1109\/tnnls.2023.3256412","type":"journal-article","created":{"date-parts":[[2023,3,23]],"date-time":"2023-03-23T17:48:59Z","timestamp":1679593739000},"page":"12316-12329","source":"Crossref","is-referenced-by-count":3,"title":["Distribution Matching for Machine Teaching"],"prefix":"10.1109","volume":"35","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7391-0334","authenticated-orcid":false,"given":"Xiaofeng","family":"Cao","sequence":"first","affiliation":[{"name":"School of Artificial Intelligence, Jilin University, Changchun, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2211-8176","authenticated-orcid":false,"given":"Ivor W.","family":"Tsang","sequence":"additional","affiliation":[{"name":"Centre for Frontier AI Research, Agency for Science, Technology and Research, Fusionopolis Way, Singapore"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/S0004-3702(98)00055-1"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1142\/9789811256943_0017"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1126\/science.aaa8415"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1023\/A:1007617005950"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1145\/1143844.1143865"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.2200\/s00196ed1v01y200906aim006"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.5555\/2188385.2188395"},{"key":"ref8","first-page":"1","article-title":"Practical Bayesian optimization of machine learning algorithms","volume-title":"Proc. NIPS","author":"Snoek"},{"key":"ref9","first-page":"315","article-title":"Accelerating stochastic gradient descent using predictive variance reduction","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"26","author":"Johnson"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1162\/evco.1993.1.1.1"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v29i1.9761"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1006\/jcss.1995.1003"},{"key":"ref13","article-title":"An overview of machine teaching","author":"Zhu","year":"2018","journal-title":"arXiv:1801.05927"},{"key":"ref14","first-page":"3147","article-title":"Towards black-box iterative machine teaching","volume-title":"Proc. 35th Int. Conf. Mach. Learn. (ICML)","author":"Liu"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2019.2934906"},{"key":"ref16","first-page":"1547","article-title":"Teaching a black-box learner","volume-title":"Proc. 36th Int. Conf. Mach. Learn. (ICML)","author":"Dasgupta"},{"issue":"1","key":"ref17","first-page":"1012","article-title":"Preference-based teaching","volume":"18","author":"Gao","year":"2017","journal-title":"J. Mach. Learn. Res."},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1007\/BF03037091"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/tnnls.2022.3168935"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/tnnls.2022.3152732"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/ICPR.2008.4761105"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58607-2_30"},{"key":"ref23","article-title":"SOLOIST: Building task bots at scale with transfer learning and machine teaching","author":"Peng","year":"2020","journal-title":"arXiv:2005.05298"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1145\/3313831.3376226"},{"key":"ref25","first-page":"353","article-title":"A general agnostic active learning algorithm","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Dasgupta"},{"key":"ref26","first-page":"1","article-title":"Machine teaching of active sequential learners","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Peltola"},{"key":"ref27","first-page":"1449","article-title":"How do humans teach: On curriculum learning and teaching dimension","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Khan"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v29i1.9569"},{"key":"ref29","first-page":"1905","article-title":"Machine teaching for Bayesian learners in the exponential family","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Zhu"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1145\/1553374.1553380"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/tnnls.2021.3112229"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1007\/BF00993277"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.3016928"},{"key":"ref34","first-page":"199","article-title":"Agnostic active learning without constraints","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Beygelzimer"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1145\/1143844.1143853"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1145\/1273496.1273541"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1145\/1553374.1553381"},{"key":"ref38","first-page":"45","article-title":"Support vector machine active learning with applications to text classification","volume":"2","author":"Tong","year":"2002","journal-title":"J. Mach. Learn. Res."},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2018.2868649"},{"issue":"1","key":"ref40","first-page":"125","article-title":"Active learning in black-box settings","volume":"40","author":"Rubens","year":"2011","journal-title":"Austrian J. Statist."},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1145\/130385.130417"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1145\/3418284"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2020.3044473"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/tnnls.2021.3135420"},{"issue":"1","key":"ref45","first-page":"5631","article-title":"The teaching dimension of linear learners","volume":"17","author":"Liu","year":"2016","journal-title":"J. Mach. Learn. Res."},{"key":"ref46","first-page":"2495","article-title":"An optimal control approach to sequential machine teaching","volume-title":"Proc. 22nd Int. Conf. Artif. Intell. Statist.","author":"Lessard"},{"key":"ref47","first-page":"2535","article-title":"On the power of curriculum learning in training deep networks","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Hacohen"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.3027605"},{"key":"ref49","first-page":"59","article-title":"Bayesian modeling of human concept learning","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Tenenbaum"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1007\/s00180-015-0641-3"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1016\/j.physleta.2006.12.019"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01096"},{"key":"ref53","first-page":"1","article-title":"Explaining and harnessing adversarial examples","volume-title":"Proc. ICLR","author":"Goodfellow"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4757-3264-1"},{"key":"ref55","first-page":"3444","article-title":"Diameter-based active learning","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Tosh"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1561\/2200000037"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2018.2874458"},{"key":"ref58","first-page":"1646","article-title":"Hyperbolic entailment cones for learning hierarchical embeddings","volume-title":"Proc. 35th Int. Conf. Mach. Learn. (ICML)","author":"Ganea"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1145\/3336191.3371850"},{"key":"ref60","first-page":"3779","article-title":"Learning continuous hierarchies in the Lorentz model of hyperbolic geometry","volume-title":"Proc. 35th Int. Conf. Mach. Learn. (ICML)","author":"Nickel"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2017.2677446"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1145\/1143844.1143980"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2016.01.035"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1007\/s10044-018-0709-0"},{"key":"ref65","first-page":"441","article-title":"Toward optimal active learning through Monte Carlo estimation of error reduction","volume-title":"Proc. Int. Conf. Mach. Learn. (ICML)","volume":"2","author":"Roy"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1145\/1390156.1390183"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33015117"}],"container-title":["IEEE Transactions on Neural Networks and Learning Systems"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/5962385\/10663876\/10079195.pdf?arnumber=10079195","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,4]],"date-time":"2024-09-04T18:13:29Z","timestamp":1725473609000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10079195\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,9]]},"references-count":67,"journal-issue":{"issue":"9"},"URL":"https:\/\/doi.org\/10.1109\/tnnls.2023.3256412","relation":{},"ISSN":["2162-237X","2162-2388"],"issn-type":[{"value":"2162-237X","type":"print"},{"value":"2162-2388","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,9]]}}}