{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,30]],"date-time":"2025-08-30T16:21:41Z","timestamp":1756570901288,"version":"3.28.0"},"reference-count":40,"publisher":"IEEE","license":[{"start":{"date-parts":[[2021,7,1]],"date-time":"2021-07-01T00:00:00Z","timestamp":1625097600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,7,1]],"date-time":"2021-07-01T00:00:00Z","timestamp":1625097600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,7,1]],"date-time":"2021-07-01T00:00:00Z","timestamp":1625097600000},"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":[[2021,7]]},"DOI":"10.1109\/icccn52240.2021.9522327","type":"proceedings-article","created":{"date-parts":[[2021,8,31]],"date-time":"2021-08-31T20:31:47Z","timestamp":1630441907000},"page":"1-9","source":"Crossref","is-referenced-by-count":4,"title":["Efficient Communication Topology via Partially Differential Privacy for Decentralized Learning"],"prefix":"10.1109","author":[{"given":"Cheng-Wei","family":"Ching","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hung-Sheng","family":"Huang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chun-An","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yu-Chun","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jian-Jhih","family":"Kuo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref39","article-title":"Decentralized stochastic optimization and gossip algorithms with compressed communication","author":"koloskova","year":"2019","journal-title":"ICML PMLR"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2019.2932876"},{"journal-title":"Efficient communication topology via partially differential privacy for decentralized learning (technical report)","year":"2021","author":"ching","key":"ref33"},{"key":"ref32","article-title":"cpSGD: Communication-efficient and differentially-private distributed SGD","author":"agarwal","year":"2018","journal-title":"NeurIPS"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1145\/3397166.3409123"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2019.2952146"},{"key":"ref37","article-title":"The non-IID data quagmire of decentralized machine learning","author":"hsieh","year":"2020","journal-title":"ICML PMLR"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2019.2935719"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2020.106622"},{"key":"ref34","article-title":"AutoSync: Learning to synchronize for data-parallel distributed deep learning","author":"zhang","year":"2020","journal-title":"NeurIPS"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1145\/3133956.3134012"},{"key":"ref40","first-page":"17","article-title":"On the evolution of random graphs","volume":"5","author":"erd?s","year":"1960","journal-title":"Publ Math Inst Hung Acad Sci"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1145\/2976749.2978318"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2018.2794384"},{"article-title":"Learning multiple layers of features from tiny images","year":"2009","author":"krizhevsky","key":"ref13"},{"key":"ref14","article-title":"Can decentralized algorithms outperform centralized algorithms? a case study for decentralized parallel stochastic gradient descent","author":"lian","year":"2017","journal-title":"NeurIPS"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/j.comnet.2020.107248"},{"key":"ref16","article-title":"MobileNets: Efficient convolutional neural networks for mobile vision applications","author":"howard","year":"2017","journal-title":"arXiv 1704 04861"},{"key":"ref17","article-title":"SqueezeNet: Alexnet-level accuracy with 50x fewer parameters and < 0.5 MB model size","author":"iandola","year":"2016","journal-title":"arXiv 1602 07360"},{"key":"ref18","article-title":"And the Bit Goes Down: Revisiting the quantization of neural networks","author":"stock","year":"2020","journal-title":"ICLRE"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/GLOCOMW.2017.8269112"},{"key":"ref28","article-title":"Pipe-SGD: A decentralized pipelined SGD framework for distributed deep net training","author":"li","year":"2018","journal-title":"NeurIPS"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2020.2975749"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TAC.1986.1104412"},{"key":"ref3","article-title":"Communication-efficient learning of deep networks from decentralized data","author":"mcmahan","year":"2017","journal-title":"AISTATS PMLR"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-96550-5_1"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2020.2988575"},{"key":"ref5","article-title":"Decentralized deep learning with arbitrary communication compression","author":"koloskova","year":"2020","journal-title":"ICLRE"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM.2019.8737367"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2017.12.002"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.comnet.2012.07.010"},{"key":"ref9","doi-asserted-by":"crossref","first-page":"953","DOI":"10.1109\/JPROC.2018.2817461","article-title":"Network topology and communication-computation tradeoffs in decentralized optimization","volume":"106","author":"nedi?","year":"2018","journal-title":"Proc of the IEEE"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2020.3018304"},{"key":"ref20","first-page":"1","article-title":"Random walks on graphs: A survey","volume":"2","author":"lov\u00e1sz","year":"1993","journal-title":"Combinatorics Paul Erdos Is Eighty"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/VTCFall.2016.7880946"},{"key":"ref21","article-title":"Subflow: A dynamic induced-subgraph strategy toward real-time dnn inference and training","author":"lee","year":"2020","journal-title":"IEEE RTAS"},{"key":"ref24","article-title":"Federated learning: Strategies for improving communication efficiency","author":"kone?n?","year":"2016","journal-title":"NeurIPS workshop"},{"key":"ref23","article-title":"Fashion-mnist: a novel image dataset for benchmarking machine learning algorithms","author":"xiao","year":"2017","journal-title":"ArXiv 1708 07747"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/ICC.2019.8761315"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/JSAC.2019.2904348"}],"event":{"name":"2021 International Conference on Computer Communications and Networks (ICCCN)","start":{"date-parts":[[2021,7,19]]},"location":"Athens, Greece","end":{"date-parts":[[2021,7,22]]}},"container-title":["2021 International Conference on Computer Communications and Networks (ICCCN)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9521949\/9522143\/09522327.pdf?arnumber=9522327","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,10]],"date-time":"2022-05-10T15:45:22Z","timestamp":1652197522000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9522327\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,7]]},"references-count":40,"URL":"https:\/\/doi.org\/10.1109\/icccn52240.2021.9522327","relation":{},"subject":[],"published":{"date-parts":[[2021,7]]}}}