{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,30]],"date-time":"2024-10-30T01:31:23Z","timestamp":1730251883214,"version":"3.28.0"},"reference-count":22,"publisher":"IEEE","license":[{"start":{"date-parts":[[2024,2,19]],"date-time":"2024-02-19T00:00:00Z","timestamp":1708300800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,2,19]],"date-time":"2024-02-19T00:00:00Z","timestamp":1708300800000},"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":[[2024,2,19]]},"DOI":"10.1109\/icnc59896.2024.10556165","type":"proceedings-article","created":{"date-parts":[[2024,6,21]],"date-time":"2024-06-21T17:20:54Z","timestamp":1718990454000},"page":"560-566","source":"Crossref","is-referenced-by-count":0,"title":["Fed2Com: Towards Efficient Compression in Federated Learning"],"prefix":"10.1109","author":[{"given":"Yu","family":"Zhang","sequence":"first","affiliation":[{"name":"The Chinese University of Hong Kong,Dept. of Computer Science and Engineering,Hong Kong"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wei","family":"Lin","sequence":"additional","affiliation":[{"name":"The Chinese University of Hong Kong,Dept. of Computer Science and Engineering,Hong Kong"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sisi","family":"Chen","sequence":"additional","affiliation":[{"name":"The Chinese University of Hong Kong,Dept. of Computer Science and Engineering,Hong Kong"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qingyu","family":"Song","sequence":"additional","affiliation":[{"name":"The Chinese University of Hong Kong,Dept. of Computer Science and Engineering,Hong Kong"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiaxun","family":"Lu","sequence":"additional","affiliation":[{"name":"Huawei Technologies Noah&#x0027;s Ark Lab,China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yunfeng","family":"Shao","sequence":"additional","affiliation":[{"name":"Huawei Technologies Noah&#x0027;s Ark Lab,China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bei","family":"Yu","sequence":"additional","affiliation":[{"name":"The Chinese University of Hong Kong,Dept. of Computer Science and Engineering,Hong Kong"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hong","family":"Xu","sequence":"additional","affiliation":[{"name":"The Chinese University of Hong Kong,Dept. of Computer Science and Engineering,Hong Kong"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","first-page":"1273","article-title":"Communication-efficient learning of deep networks from decentralized data","author":"McMahan","year":"2017","journal-title":"Artificial intelligence and statistics"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1561\/2200000083"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.23919\/WiOpt52861.2021.9589061"},{"journal-title":"Scaffold: Stochastic controlled averaging for on-device federated learning","year":"2019","author":"Karimireddy","key":"ref4"},{"key":"ref5","first-page":"3","article-title":"On the convergence of federated optimization in heterogeneous networks","volume":"3","author":"Sahu","year":"2018","journal-title":"arXiv preprint"},{"key":"ref6","article-title":"On biased compression for distributed learning","author":"Beznosikov","year":"2020","journal-title":"arXiv preprint"},{"key":"ref7","article-title":"Cooperative sgd: A unified framework for the design and analysis of communication-efficient sgd algorithms","author":"Wang","year":"2018","journal-title":"arXiv preprint"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/ICDCS.2019.00099"},{"key":"ref9","first-page":"8253","article-title":"Fetchsgd: Communication-efficient feder-ated learning with sketching","volume-title":"International Conference on Machine Learning","author":"Rothchild"},{"key":"ref10","article-title":"Qsgd: Communication-efficient sgd via gradient quantization and encoding","volume":"30","author":"Alistarh","year":"2017","journal-title":"Advances in neural information processing systems"},{"key":"ref11","article-title":"Gradient sparsification for communication-efficient distributed optimization","volume":"31","author":"Wangni","year":"2018","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref12","article-title":"A better alternative to error feed-back for communication-efficient distributed learning","author":"Horv\u00e1th","year":"2020","journal-title":"arXiv preprint"},{"key":"ref13","article-title":"Deep gradient compression: Reducing the communication bandwidth for distributed training","author":"Lin","year":"2017","journal-title":"arXiv preprint"},{"key":"ref14","first-page":"560","article-title":"signsgd: Compressed optimisation for non-convex problems","volume-title":"International Conference on Machine Learning","author":"Bernstein"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"journal-title":"Learning multiple layers of features from tiny images","year":"2009","author":"Krizhevsky","key":"ref16"},{"key":"ref17","first-page":"7184","article-title":"On the linear speedup analysis of communication efficient momentum sgd for distributed non-convex optimization","volume-title":"International Conference on Machine Learning","author":"Yu"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"key":"ref19","article-title":"Distilbert, a distilled version of bert: smaller, faster, cheaper and lighter","author":"Sanh","year":"2019","journal-title":"arXiv preprint"},{"issue":"12","key":"ref20","first-page":"2009","article-title":"Twitter sentiment classification using distant supervision","volume":"1","author":"Go","year":"2009","journal-title":"CS224N project report, Stanford"},{"issue":"8","key":"ref21","first-page":"9","article-title":"Language models are unsupervised multitask learners","volume":"1","author":"Radford","year":"2019","journal-title":"OpenAI blog"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P18-1205"}],"event":{"name":"2024 International Conference on Computing, Networking and Communications (ICNC)","start":{"date-parts":[[2024,2,19]]},"location":"Big Island, HI, USA","end":{"date-parts":[[2024,2,22]]}},"container-title":["2024 International Conference on Computing, Networking and Communications (ICNC)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/10555566\/10555889\/10556165.pdf?arnumber=10556165","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,6,25]],"date-time":"2024-06-25T19:15:42Z","timestamp":1719342942000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10556165\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,2,19]]},"references-count":22,"URL":"https:\/\/doi.org\/10.1109\/icnc59896.2024.10556165","relation":{},"subject":[],"published":{"date-parts":[[2024,2,19]]}}}