{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,13]],"date-time":"2026-10-13T17:44:59Z","timestamp":1791913499809,"version":"4.3.4"},"reference-count":31,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"4","license":[{"start":{"date-parts":[[2025,4,1]],"date-time":"2025-04-01T00:00:00Z","timestamp":1743465600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,4,1]],"date-time":"2025-04-01T00:00:00Z","timestamp":1743465600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,4,1]],"date-time":"2025-04-01T00:00:00Z","timestamp":1743465600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"Government of India and Hewlett Packard Enterprise India","award":["DST Core Research Grant"],"award-info":[{"award-number":["DST Core Research Grant"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Artif. Intell."],"published-print":{"date-parts":[[2025,4]]},"DOI":"10.1109\/tai.2024.3506494","type":"journal-article","created":{"date-parts":[[2024,11,27]],"date-time":"2024-11-27T14:52:31Z","timestamp":1732719151000},"page":"968-978","source":"Crossref","is-referenced-by-count":1,"title":["CheckSelect: Online Checkpoint Selection for Flexible, Accurate, Robust, and Efficient Data Valuation"],"prefix":"10.1109","volume":"6","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6933-5744","authenticated-orcid":false,"given":"Soumi","family":"Das","sequence":"first","affiliation":[{"name":"Indian Institute of Technology Kharagpur, Kharagpur, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3530-6352","authenticated-orcid":false,"given":"Manasvi","family":"Sagarkar","sequence":"additional","affiliation":[{"name":"Indian Institute of Technology Kharagpur, Kharagpur, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9541-4027","authenticated-orcid":false,"given":"Suparna","family":"Bhattacharya","sequence":"additional","affiliation":[{"name":"AI Research Lab, Hewlett Packard Labs, Bangalore, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5220-1881","authenticated-orcid":false,"given":"Sourangshu","family":"Bhattacharya","sequence":"additional","affiliation":[{"name":"Indian Institute of Technology Kharagpur, Kharagpur, India"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","first-page":"20596","article-title":"Deep learning on a data diet: Finding important examples early in training","volume":"34","author":"Paul","year":"2021","journal-title":"Proc. 35th Int. Conf. Neural Inf. Process. Syst."},{"key":"ref2","article-title":"GRAD-MATCH: A gradient matching based data subset selection for efficient learning","author":"Killamsetty","year":"2021"},{"key":"ref3","first-page":"10842","article-title":"Data valuation using reinforcement learning","volume-title":"Proc. 37th Int. Conf. Mach. Learn.","author":"Yoon","year":"2020"},{"key":"ref4","first-page":"19920","article-title":"Estimating training data influence by tracing gradient descent","author":"Pruthi","year":"2020","journal-title":"Proc. 34th Int. Conf. Neural Inf. Process. Syst."},{"key":"ref5","article-title":"Active learning for convolutional neural networks: A core-set approach","author":"Sener","year":"2017"},{"key":"ref6","first-page":"1885","article-title":"Understanding black-box predictions via influence functions","author":"Koh","year":"2017","journal-title":"Proc. 34th Int. Conf. Mach. Learn."},{"key":"ref7","first-page":"2242","article-title":"Data Shapley: Equitable valuation of data for machine learning","author":"Ghorbani","year":"2019","journal-title":"Proc. 36th Int. Conf. Mach. Learn."},{"key":"ref8","first-page":"6950","article-title":"Coresets for data-efficient training of machine learning models","volume-title":"Proc. 37th Int. Conf. Mach. Learn.","author":"Mirzasoleiman","year":"2020"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-86520-7_41"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2004.834793"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2007.909108"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/SSP.2012.6319766"},{"key":"ref13","article-title":"Online orthogonal matching pursuit","author":"Saad","year":"2021"},{"issue":"161","key":"ref14","first-page":"1","article-title":"apricot: Submodular selection for data summarization in Python.","volume":"21","author":"Schreiber","year":"2020","journal-title":"J. Mach. Learn. Res."},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.572"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-12423-5_14"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58607-2_16"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-022-06194-9"},{"key":"ref19","article-title":"Dataset distillation","author":"Wang","year":"2018"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00708"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00137"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.197"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00628"},{"key":"ref24","article-title":"Learning multiple layers of features from tiny images","author":"Krizhevsky","year":"2009"},{"issue":"7","key":"ref25","first-page":"3","article-title":"Tiny imagenet visual recognition challenge","volume":"7","author":"Le","year":"2015","journal-title":"CS 231N"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1016\/B978-1-55860-377-6.50048-7"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1016\/S0167-7152(96)00140-X"},{"key":"ref28","article-title":"Multivariate Gait Data","volume-title":"UCI Machine Learning Repository","author":"Helwig","year":"2016"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00151"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.emnlp-main.746"}],"container-title":["IEEE Transactions on Artificial Intelligence"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/9078688\/10946214\/10770189.pdf?arnumber=10770189","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,23]],"date-time":"2025-08-23T01:09:46Z","timestamp":1755911386000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10770189\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,4]]},"references-count":31,"journal-issue":{"issue":"4"},"URL":"https:\/\/doi.org\/10.1109\/tai.2024.3506494","relation":{},"ISSN":["2691-4581"],"issn-type":[{"value":"2691-4581","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,4]]}}}