{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,3]],"date-time":"2026-03-03T09:39:14Z","timestamp":1772530754048,"version":"3.50.1"},"reference-count":44,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"9","license":[{"start":{"date-parts":[[2021,9,1]],"date-time":"2021-09-01T00:00:00Z","timestamp":1630454400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,9,1]],"date-time":"2021-09-01T00:00:00Z","timestamp":1630454400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,9,1]],"date-time":"2021-09-01T00:00:00Z","timestamp":1630454400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61702188"],"award-info":[{"award-number":["61702188"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["11871279"],"award-info":[{"award-number":["11871279"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003399","name":"General Program of Shanghai Science and Technology Commission","doi-asserted-by":"publisher","award":["19ZR1414200"],"award-info":[{"award-number":["19ZR1414200"]}],"id":[{"id":"10.13039\/501100003399","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"NSFC-Zhejiang Joint Fund for the Integration of Industrialization and Information","doi-asserted-by":"publisher","award":["U1609220"],"award-info":[{"award-number":["U1609220"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Cybern."],"published-print":{"date-parts":[[2021,9]]},"DOI":"10.1109\/tcyb.2019.2950337","type":"journal-article","created":{"date-parts":[[2019,12,30]],"date-time":"2019-12-30T20:24:30Z","timestamp":1577737470000},"page":"4540-4552","source":"Crossref","is-referenced-by-count":25,"title":["Distributed and Parallel ADMM for Structured Nonconvex Optimization Problem"],"prefix":"10.1109","volume":"51","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3064-5128","authenticated-orcid":false,"given":"Xiangfeng","family":"Wang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9639-7679","authenticated-orcid":false,"given":"Junchi","family":"Yan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1028-5989","authenticated-orcid":false,"given":"Bo","family":"Jin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2985-1098","authenticated-orcid":false,"given":"Wenhao","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.2307\/2348496"},{"key":"ref38","first-page":"288","article-title":"LWPR: An $O(n)$\n algorithm for incremental real time learning in high dimensional space","author":"vijayakumar","year":"2000","journal-title":"Proc ICML"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1137\/17M1146567"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1007\/s10107-016-1057-8"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1137\/140990309"},{"key":"ref30","first-page":"1701","article-title":"Asynchronous distributed ADMM for consensus optimization","author":"zhang","year":"2014","journal-title":"Proc ICML"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1214\/09-AOS729"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1198\/016214501753382273"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2015.9"},{"key":"ref34","first-page":"284","article-title":"Efficient sparse group feature selection via nonconvex optimization","author":"xiang","year":"2013","journal-title":"Proc ICML"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2015.2511584"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.3115\/1620754.1620794"},{"key":"ref11","first-page":"361","article-title":"Multi-level lasso for sparse multi-task regression","author":"swirszcz","year":"2012","journal-title":"Proc ICML"},{"key":"ref12","first-page":"964","article-title":"A dirty model for multi-task learning","author":"jalali","year":"2010","journal-title":"Proc NeurIPS"},{"key":"ref13","first-page":"42","article-title":"Integrating low-rank and group-sparse structures for robust MTL","author":"chen","year":"2011","journal-title":"Proc ACM SIGKDD"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1145\/2339530.2339672"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1007\/s10107-010-0394-2"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1137\/080716542"},{"key":"ref17","volume":"87","author":"nesterov","year":"2013","journal-title":"Introductory Lectures on Convex Optimization A Basic Course"},{"key":"ref18","first-page":"1458","article-title":"Convergence rates of inexact proximal-gradient methods for convex optimization","author":"schmidt","year":"2011","journal-title":"Proc NeurIPS"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1137\/151004549"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1007\/s10589-016-9828-y"},{"key":"ref4","first-page":"2202","article-title":"Sparse overlapping sets lasso for multitask learning and its application to fMRI analysis","author":"rao","year":"2013","journal-title":"Proc NeurIPS"},{"key":"ref27","first-page":"619","article-title":"Understanding the convergence of the ADMM: Theoretical and computational perspectives","volume":"11","author":"eckstein","year":"2015","journal-title":"Pac J Optim"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-10578-9_28"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1137\/090763184"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1088\/0266-5611\/28\/11\/115010"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-007-5040-8"},{"key":"ref8","first-page":"803","article-title":"A new approach to collaborative filtering: Operator estimation with spectral regularization","volume":"10","author":"abernethy","year":"2009","journal-title":"J Mach Learn Res"},{"key":"ref7","first-page":"339","article-title":"Multi-task feature learning via efficient $\\ell_{2,1}$\n-norm minimization","author":"liu","year":"2009","journal-title":"Proc UAI"},{"key":"ref2","first-page":"1209","article-title":"Multi-task learning for subspace segmentation","author":"wang","year":"2015","journal-title":"Proc ICML"},{"key":"ref9","author":"gong","year":"2013","journal-title":"Gist General iterative shrinkage and thresholding for non-convex sparse learning"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939857"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1007\/s10107-011-0484-9"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1137\/130942954"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1007\/s10107-013-0701-9"},{"key":"ref42","author":"brockman","year":"2016","journal-title":"OpenAI Gym"},{"key":"ref24","first-page":"37","article-title":"A general iterative shrinkage and thresholding algorithm for non-convex regularized optimization problems","author":"gong","year":"2013","journal-title":"Proc ICML"},{"key":"ref41","first-page":"819","article-title":"Sparse multi-task reinforcement learning","author":"calandriello","year":"2014","journal-title":"Proc NeurIPS"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1007\/s10915-017-0376-0"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1007\/s10957-019-01565-0"},{"key":"ref26","first-page":"41","article-title":"Sur l&#x2019;approximation, par &#x00E9;l&#x00E9;ments finis d&#x2019;ordre un, et la r&#x00E9;solution, par p&#x00E9;nalisation-dualit&#x00E9; d&#x2019;une classe de probl&#x00E9;mes de Dirichlet non lin&#x00E9;aires","volume":"9","author":"glowinski","year":"1975","journal-title":"ESAIM Math Model Numer Anal"},{"key":"ref43","first-page":"1313","article-title":"Weighted sums of random kitchen sinks: Replacing minimization with randomization in learning","author":"rahimi","year":"2009","journal-title":"Proc NeurIPS"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1561\/2200000016"}],"container-title":["IEEE Transactions on Cybernetics"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6221036\/9539103\/08945408.pdf?arnumber=8945408","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,10]],"date-time":"2022-05-10T14:53:37Z","timestamp":1652194417000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8945408\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,9]]},"references-count":44,"journal-issue":{"issue":"9"},"URL":"https:\/\/doi.org\/10.1109\/tcyb.2019.2950337","relation":{},"ISSN":["2168-2267","2168-2275"],"issn-type":[{"value":"2168-2267","type":"print"},{"value":"2168-2275","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,9]]}}}