{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,4]],"date-time":"2026-04-04T18:03:59Z","timestamp":1775325839801,"version":"3.50.1"},"reference-count":25,"publisher":"IEEE","license":[{"start":{"date-parts":[[2023,5,17]],"date-time":"2023-05-17T00:00:00Z","timestamp":1684281600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,5,17]],"date-time":"2023-05-17T00:00:00Z","timestamp":1684281600000},"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":[[2023,5,17]]},"DOI":"10.1109\/infocom53939.2023.10229075","type":"proceedings-article","created":{"date-parts":[[2023,8,29]],"date-time":"2023-08-29T13:40:43Z","timestamp":1693316443000},"page":"1-10","source":"Crossref","is-referenced-by-count":50,"title":["Asynchronous Federated Unlearning"],"prefix":"10.1109","author":[{"given":"Ningxin","family":"Su","sequence":"first","affiliation":[{"name":"University of Toronto,Department of Electrical and Computer Engineering"}]},{"given":"Baochun","family":"Li","sequence":"additional","affiliation":[{"name":"University of Toronto,Department of Electrical and Computer Engineering"}]}],"member":"263","reference":[{"key":"ref13","first-page":"2008","article-title":"Approximate Data Deletion from Machine Learning Models","author":"izzo","year":"2021","journal-title":"Proc 24th Int’l Conference on Artificial Intelligence and Statistics (AISTATS)"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58526-6_23"},{"key":"ref15","article-title":"Certified data removal from machine learning models","author":"guo","year":"2019"},{"key":"ref14","first-page":"931","article-title":"Descent-to-Delete: Gradient-Based Methods for Machine Unlearning","author":"neel","year":"2021","journal-title":"Proc 32nd Int’l Conference on Algorithmic Learning Theory"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00932"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2015.35"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/IWQOS52092.2021.9521274"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/SP40001.2021.00019"},{"key":"ref17","first-page":"1092","article-title":"Machine Unlearning for Random Forests","author":"brophy","year":"2021","journal-title":"Proc of the International Conference on Machine Learning (ICML)"},{"key":"ref16","article-title":"Making AI Forget You: Data Deletion in Machine Learning","author":"ginart","year":"2019","journal-title":"Advances in Neural Information Processing Systems (NeurIPS 2019)"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1145\/3485447.3512222"},{"key":"ref18","article-title":"Federated Unlearning with Knowledge Distillation","author":"wu","year":"2022"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-018-3523-0"},{"key":"ref23","article-title":"LEAF: A Benchmark for Federated Settings","author":"caldas","year":"2018"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.emnlp-demos.6"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i12.17275"},{"key":"ref22","article-title":"Learning Multiple Layers of Features from Tiny Images","author":"krizhevsky","year":"2009","journal-title":"Tech Rep"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"key":"ref8","first-page":"1273","article-title":"Communication-Efficient Learning of Deep Networks from Decentralized Data","volume":"54","author":"mcmahan","year":"2017","journal-title":"Proc 20th Int’l Conference on Artificial Intelligence and Statistics (AISTATS)"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM48880.2022.9796721"},{"key":"ref9","article-title":"Asynchronous Federated Optimization","author":"xie","year":"2020","journal-title":"Proc NeurIPS Workshop on Optimization for Machine Learning (OPT)"},{"key":"ref4","article-title":"Federated Learning with Buffered Asynchronous Aggregation","author":"nguyen","year":"2021","journal-title":"Proc of the International Conference on Machine Learning (ICML)"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/IWQoS54832.2022.9812885"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1137\/0315059"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM41043.2020.9155494"}],"event":{"name":"IEEE INFOCOM 2023 - IEEE Conference on Computer Communications","location":"New York City, NY, USA","start":{"date-parts":[[2023,5,17]]},"end":{"date-parts":[[2023,5,20]]}},"container-title":["IEEE INFOCOM 2023 - IEEE Conference on Computer Communications"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/10228851\/10228852\/10229075.pdf?arnumber=10229075","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,18]],"date-time":"2023-09-18T13:44:05Z","timestamp":1695044645000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10229075\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,5,17]]},"references-count":25,"URL":"https:\/\/doi.org\/10.1109\/infocom53939.2023.10229075","relation":{},"subject":[],"published":{"date-parts":[[2023,5,17]]}}}