{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,26]],"date-time":"2025-11-26T16:46:42Z","timestamp":1764175602604,"version":"build-2065373602"},"reference-count":26,"publisher":"IEEE","license":[{"start":{"date-parts":[[2024,4,14]],"date-time":"2024-04-14T00:00:00Z","timestamp":1713052800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,4,14]],"date-time":"2024-04-14T00:00:00Z","timestamp":1713052800000},"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":[[2024,4,14]]},"DOI":"10.1109\/icassp48485.2024.10446222","type":"proceedings-article","created":{"date-parts":[[2024,3,18]],"date-time":"2024-03-18T18:56:31Z","timestamp":1710788191000},"page":"7575-7579","source":"Crossref","is-referenced-by-count":6,"title":["Communication Efficient Private Federated Learning Using Dithering"],"prefix":"10.1109","author":[{"given":"Burak","family":"Has\u0131rc\u0131o\u011flu","sequence":"first","affiliation":[{"name":"Information Processing and Communications Lab,Imperial College,London,UK"}]},{"given":"Deniz","family":"G\u00fcnd\u00fcz","sequence":"additional","affiliation":[{"name":"Information Processing and Communications Lab,Imperial College,London,UK"}]}],"member":"263","reference":[{"key":"ref1","first-page":"1273","article-title":"Communication-Efficient Learning of Deep Networks from Decentralized Data","volume-title":"Proc. of Int\u2019l Conf. on Artificial Int. and Stats","author":"McMahan"},{"key":"ref2","first-page":"16937","article-title":"Inverting gradients - how easy is it to break privacy in federated learning?","volume-title":"Advances in Neural Information Processing Systems","volume":"33","author":"Geiping"},{"key":"ref3","first-page":"267","article-title":"The secret sharer: Evaluating and testing unintended memorization in neural networks","volume-title":"28th USENIX Security Symposium (USENIX Security 19)","author":"Carlini"},{"key":"ref4","first-page":"22911","article-title":"Reconstructing training data from trained neural networks","volume-title":"Advances in Neural Information Processing Systems","volume":"35","author":"Haim"},{"key":"ref5","first-page":"394","article-title":"Improving the gaussian mechanism for differential privacy: Analytical calibration and optimal denoising","volume-title":"International Conference on Machine Learning","author":"Balle"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1561\/0400000042"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/3458864.3466628"},{"key":"ref8","first-page":"3581","article-title":"Federated learning with buffered asynchronous aggregation","volume-title":"Int\u2019l Conf. on Artificial Int. and Stats","author":"Nguyen"},{"key":"ref9","first-page":"1","article-title":"Natural compression for distributed deep learning","volume-title":"Proceedings of Machine Learning Research vol","volume":"145","author":"Horv\u00e1th"},{"key":"ref10","article-title":"Qsgd: Communication-efficient sgd via gradient quantization and encoding","volume-title":"Advances in neural information processing systems","volume":"30","author":"Alistarh"},{"key":"ref11","first-page":"3329","article-title":"Distributed mean estimation with limited communication","volume-title":"Int\u2019l Conf. on Machine Learning","author":"Suresh"},{"key":"ref12","first-page":"2","article-title":"Compressive differentially private federated learning through universal vector quantization","volume-title":"AAAI Workshop on Privacy-Preserving Artificial Intelligence","author":"Amiri"},{"article-title":"Dp-rec: Private & communication-efficient federated learning","year":"2021","author":"Triastcyn","key":"ref13"},{"key":"ref14","first-page":"296","article-title":"Privacy-aware compression for federated data analysis","author":"Chaudhuri","year":"2022","journal-title":"Uncertainty in Artificial Intelligence"},{"key":"ref15","first-page":"7680","article-title":"Optimal compression of locally differentially private mechanisms","volume-title":"International Conference on Artificial Intelligence and Statistics","author":"Shah"},{"article-title":"Fast optimal locally private mean estimation via random projections","year":"2023","author":"Asi","key":"ref16"},{"article-title":"Exact optimality of communication-privacy-utility tradeoffs in distributed mean estimation","year":"2023","author":"Isik","key":"ref17"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1080\/02664769922386"},{"issue":"5","key":"ref19","first-page":"355","article-title":"Quantization and dither: A theoretical survey","volume":"40","author":"Lipshitz","year":"1992","journal-title":"Journal of the audio engineering society"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.1962.1057702"},{"key":"ref21","article-title":"Privacy amplification by sub-sampling: Tight analyses via couplings and divergences","volume-title":"Advances in neural information processing systems","volume":"31","author":"Balle"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"article-title":"Opacus: User-friendly differential privacy library in PyTorch","year":"2021","author":"Yousefpour","key":"ref24"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1145\/2976749.2978318"},{"article-title":"Renyi differential privacy of the sampled Gaussian mechanism","year":"2019","author":"Mironov","key":"ref26"}],"event":{"name":"ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","start":{"date-parts":[[2024,4,14]]},"location":"Seoul, Korea, Republic of","end":{"date-parts":[[2024,4,19]]}},"container-title":["ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/10445798\/10445803\/10446222.pdf?arnumber=10446222","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,11]],"date-time":"2024-09-11T04:45:28Z","timestamp":1726029928000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10446222\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,4,14]]},"references-count":26,"URL":"https:\/\/doi.org\/10.1109\/icassp48485.2024.10446222","relation":{},"subject":[],"published":{"date-parts":[[2024,4,14]]}}}