{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,11]],"date-time":"2026-02-11T20:49:32Z","timestamp":1770842972203,"version":"3.50.1"},"reference-count":18,"publisher":"IEEE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016,3]]},"DOI":"10.1109\/icassp.2016.7472065","type":"proceedings-article","created":{"date-parts":[[2016,6,24]],"date-time":"2016-06-24T01:58:30Z","timestamp":1466733510000},"page":"2189-2193","source":"Crossref","is-referenced-by-count":38,"title":["Randomized requantization with local differential privacy"],"prefix":"10.1109","author":[{"given":"Sijie","family":"Xiong","sequence":"first","affiliation":[]},{"given":"Anand D.","family":"Sarwate","sequence":"additional","affiliation":[]},{"given":"Narayan B.","family":"Mandayam","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/ALLERTON.2014.7028550"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1198\/jasa.2009.tm08651"},{"key":"ref12","article-title":"The composition theorem for differential privacy","author":"kairouz","year":"2015","journal-title":"Tech Rep arXiv 1311 0776v4 [cs DS] ArXiV"},{"key":"ref13","first-page":"459","article-title":"Time series compressibility and privacy","author":"papadimitriou","year":"2007","journal-title":"Proceedings of the 33rd International Conference on Very Large Data Bases VLDB Endowment"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1145\/1559845.1559850"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511804441"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.1982.1056489"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.1960.1057548"},{"key":"ref18","first-page":"41","article-title":"Private convex empirical risk minimization and high-dimensional regression","volume":"1","author":"kifer","year":"2012","journal-title":"Journal of Machine Learning Research"},{"key":"ref4","doi-asserted-by":"crossref","DOI":"10.1007\/11681878_14","article-title":"Calibrating noise to sensitivity in private data analysis","author":"dwork","year":"2006","journal-title":"Springer Berlin Heidelberg Theory of Cryptography"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1145\/1807167.1807247"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1145\/1806689.1806787"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2013.96"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/ISIT.2009.5205863"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/2043621.2043626"},{"key":"ref2","doi-asserted-by":"crossref","first-page":"2","DOI":"10.29012\/jpc.v1i2.570","article-title":"Differential privacy for statistics: What we know and what we want to learn","volume":"1","author":"dwork","year":"2010","journal-title":"Journal of Privacy and Confidentiality"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1561\/0400000042"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/FOCS.2013.53"}],"event":{"name":"2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","location":"Shanghai","start":{"date-parts":[[2016,3,20]]},"end":{"date-parts":[[2016,3,25]]}},"container-title":["2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/7465907\/7471614\/07472065.pdf?arnumber=7472065","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,9,10]],"date-time":"2019-09-10T04:10:10Z","timestamp":1568088610000},"score":1,"resource":{"primary":{"URL":"http:\/\/ieeexplore.ieee.org\/document\/7472065\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,3]]},"references-count":18,"URL":"https:\/\/doi.org\/10.1109\/icassp.2016.7472065","relation":{},"subject":[],"published":{"date-parts":[[2016,3]]}}}