{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,15]],"date-time":"2026-01-15T22:23:27Z","timestamp":1768515807325,"version":"3.49.0"},"reference-count":31,"publisher":"IEEE","license":[{"start":{"date-parts":[[2022,5,23]],"date-time":"2022-05-23T00:00:00Z","timestamp":1653264000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,5,23]],"date-time":"2022-05-23T00:00:00Z","timestamp":1653264000000},"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":[[2022,5,23]]},"DOI":"10.1109\/icassp43922.2022.9746975","type":"proceedings-article","created":{"date-parts":[[2022,4,27]],"date-time":"2022-04-27T19:50:34Z","timestamp":1651089034000},"page":"4118-4122","source":"Crossref","is-referenced-by-count":20,"title":["An Efficient DP-SGD Mechanism for Large Scale NLU Models"],"prefix":"10.1109","author":[{"given":"Christophe","family":"Dupuy","sequence":"first","affiliation":[{"name":"Amazon Alexa AI,Cambridge,MA,USA"}]},{"given":"Radhika","family":"Arava","sequence":"additional","affiliation":[{"name":"Amazon Alexa AI,Cambridge,MA,USA"}]},{"given":"Rahul","family":"Gupta","sequence":"additional","affiliation":[{"name":"Amazon Alexa AI,Cambridge,MA,USA"}]},{"given":"Anna","family":"Rumshisky","sequence":"additional","affiliation":[{"name":"Amazon Alexa AI,Cambridge,MA,USA"}]}],"member":"263","reference":[{"key":"ref31","article-title":"Preventing Overfitting in Deep Learning Using Differential Privacy","author":"khatri","year":"2017","journal-title":"Ph D thesis"},{"key":"ref30","article-title":"Horovod: Fast and easy distributed deep learning in TensorFlow","author":"sergeev","year":"0","journal-title":"arXiv 1802 05799"},{"key":"ref10","article-title":"Membership inference attack against differentially private deep learning model","author":"rahman","year":"2018","journal-title":"TDP"},{"key":"ref11","first-page":"1895","article-title":"Evaluating differentially private machine learning in practice","author":"jayaraman","year":"2019","journal-title":"USENIX Security Symposium"},{"key":"ref12","article-title":"Learning differentially private recurrent language models","author":"mcmahan","year":"0","journal-title":"arXiv 1710 06963"},{"key":"ref13","article-title":"Differentially private generative adversarial network","author":"xie","year":"0","journal-title":"arXiv 1802 06739"},{"key":"ref14","article-title":"Understanding gradient clipping in private sgd: A geometric perspective","volume":"33","author":"chen","year":"2020","journal-title":"NeurIPS"},{"key":"ref15","article-title":"cpsgd: Communication-efficient and differentially-private distributed sgd","author":"agarwal","year":"0","journal-title":"arXiv 1805 10559"},{"key":"ref16","article-title":"Differentially private learning with adaptive clipping","author":"thakkar","year":"0","journal-title":"arXiv 1905 03871"},{"key":"ref17","article-title":"Towards demystifying membership inference attacks","author":"truex","year":"0","journal-title":"arXiv 1807 09173"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.14722\/ndss.2019.23119"},{"key":"ref19","article-title":"A general approach to adding differential privacy to iterative training procedures","author":"mcmahan","year":"0","journal-title":"arXiv 1812 06210"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.21437\/Interspeech.2014-564"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611975482.151"},{"key":"ref27","article-title":"Advances in pre-training distributed word representations","author":"mikolov","year":"2018","journal-title":"LREC"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2017.41"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1145\/2976749.2978318"},{"key":"ref29","article-title":"Mxnet: A flexible and efficient machine learning library for heterogeneous distributed systems","author":"chen","year":"0","journal-title":"arXiv 1512 01274"},{"key":"ref5","article-title":"Differential privacy defenses and sampling attacks for membership inference","volume":"13","author":"rahimian","year":"2019","journal-title":"PriML Workshop (PriML)"},{"key":"ref8","article-title":"Federated learning of deep networks using model averaging","author":"mcmahan","year":"0","journal-title":"arXiv 1602 05629"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1007\/11681878_14"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/N19-1078"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2019.00019"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1145\/3331184.3331341"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/SLT.2018.8639519"},{"key":"ref22","article-title":"Snips voice platform: An embedded spoken language understanding system for private-by-design voice interfaces","author":"coucke","year":"0","journal-title":"arXiv 1805 10190"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.3115\/116580.116613"},{"key":"ref24","article-title":"Bert: Pre-training of deep bidirectional transformers for language understanding","author":"devlin","year":"0","journal-title":"arXiv 1810 04805"},{"key":"ref23","article-title":"Benchmarking natural language understanding services for building conversational agents","author":"swietojanski x liu","year":"2019","journal-title":"IWSDS"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P16-1101"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/N18-1202"}],"event":{"name":"ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","location":"Singapore, Singapore","start":{"date-parts":[[2022,5,23]]},"end":{"date-parts":[[2022,5,27]]}},"container-title":["ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9745891\/9746004\/09746975.pdf?arnumber=9746975","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,8,22]],"date-time":"2022-08-22T20:11:56Z","timestamp":1661199116000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9746975\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,5,23]]},"references-count":31,"URL":"https:\/\/doi.org\/10.1109\/icassp43922.2022.9746975","relation":{},"subject":[],"published":{"date-parts":[[2022,5,23]]}}}