{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,23]],"date-time":"2025-12-23T10:03:08Z","timestamp":1766484188884},"reference-count":13,"publisher":"IEEE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,10,18]]},"DOI":"10.23919\/wiopt52861.2021.9589776","type":"proceedings-article","created":{"date-parts":[[2021,11,8]],"date-time":"2021-11-08T23:23:56Z","timestamp":1636413836000},"page":"1-8","source":"Crossref","is-referenced-by-count":15,"title":["How Valuable Is Your Data? Optimizing Client Recruitment in Federated Learning"],"prefix":"10.23919","author":[{"given":"Yichen","family":"Ruan","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaoxi","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Carlee","family":"Joe-Wong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"journal-title":"Data selection for federated learning with relevant and irrelevant data at clients","year":"2020","author":"tuor","key":"ref10"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/JSAC.2019.2904348"},{"key":"ref12","article-title":"Scheduling policies for federated learning in wireless networks","author":"yang","year":"2019","journal-title":"IEEE Transactions on Communications"},{"journal-title":"Applied Federated Learning Improving Google Keyboard Query Suggestions","year":"2018","author":"yang","key":"ref13"},{"journal-title":"Knapsack Problems Algorithms and Computer Implementations","year":"1990","author":"martello","key":"ref4"},{"journal-title":"On the convergence of FEDAVG on non-IID data","year":"2019","author":"li","key":"ref3"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1175\/JTECH-D-11-00103.1"},{"journal-title":"Communication-efficient learning of deep networks from decentralized data","year":"2016","author":"mcmahan","key":"ref5"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1016\/0047-259X(84)90036-8"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/ICC.2019.8761315"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1145\/3139457"},{"journal-title":"Client selection in federated learning Convergence analysis and power-of-choice selection strategies","year":"2020","author":"cho","key":"ref1"},{"key":"ref9","first-page":"4424","article-title":"Federated multi-task learning","author":"smith","year":"2017","journal-title":"Advances in neural information processing systems"}],"event":{"name":"2021 19th International Symposium on Modeling and Optimization in Mobile, Ad hoc, and Wireless Networks (WiOpt)","start":{"date-parts":[[2021,10,18]]},"location":"Philadelphia, PA, USA","end":{"date-parts":[[2021,10,21]]}},"container-title":["2021 19th International Symposium on Modeling and Optimization in Mobile, Ad hoc, and Wireless Networks (WiOpt)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9588334\/9589050\/09589776.pdf?arnumber=9589776","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,3,14]],"date-time":"2022-03-14T22:38:48Z","timestamp":1647297528000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9589776\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,10,18]]},"references-count":13,"URL":"https:\/\/doi.org\/10.23919\/wiopt52861.2021.9589776","relation":{},"subject":[],"published":{"date-parts":[[2021,10,18]]}}}