{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,27]],"date-time":"2025-10-27T20:43:59Z","timestamp":1761597839391,"version":"3.37.3"},"reference-count":43,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"12","license":[{"start":{"date-parts":[[2017,12,1]],"date-time":"2017-12-01T00:00:00Z","timestamp":1512086400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"}],"funder":[{"DOI":"10.13039\/501100001824","name":"Grant Agency of the Czech Republic","doi-asserted-by":"publisher","award":["GBP103\/12\/G084"],"award-info":[{"award-number":["GBP103\/12\/G084"]}],"id":[{"id":"10.13039\/501100001824","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Parallel Distrib. Syst."],"published-print":{"date-parts":[[2017,12,1]]},"DOI":"10.1109\/tpds.2017.2731764","type":"journal-article","created":{"date-parts":[[2017,7,25]],"date-time":"2017-07-25T14:22:47Z","timestamp":1500992567000},"page":"3330-3343","source":"Crossref","is-referenced-by-count":15,"title":["A GPU-Architecture Optimized Hierarchical Decomposition Algorithm for Support Vector Machine Training"],"prefix":"10.1109","volume":"28","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2639-6731","authenticated-orcid":false,"given":"Jan","family":"Vanek","sequence":"first","affiliation":[]},{"given":"Josef","family":"Michalek","sequence":"additional","affiliation":[]},{"given":"Josef","family":"Psutka","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-29347-4_51"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1145\/2020408.2020548"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.2478\/s13537-011-0028-7"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1145\/1735688.1735692"},{"key":"ref31","first-page":"1","article-title":"cuSVM: A CUDA implementation of support vector classification and regression","author":"carpenter","year":"2009","journal-title":"patternsonscreen net\/ cuSVMDesc pdf"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1145\/1390156.1390170"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/ICMLA.2010.53"},{"key":"ref36","article-title":"Parallel support vector machines in practice","author":"tyree","year":"2014","journal-title":"arXiv 1404 1066"},{"key":"ref35","first-page":"355","article-title":"GPUMLib: An efficient open-source GPU machine learning library","volume":"3","author":"lopes","year":"2011","journal-title":"Int J Comput Inf Syst Ind Manage Appl"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1016\/j.jpdc.2012.02.011"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2013.2279167"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1142\/S0218213014500122"},{"article-title":"Optimization algorithms in support vector machines","year":"2009","author":"wright","key":"ref11"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1137\/S1052623400374379"},{"article-title":"Online learning: Theory, algorithms, and applications","year":"2007","author":"shalev-shwartz","key":"ref13"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1145\/1390156.1390208"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1145\/1150402.1150429"},{"key":"ref16","first-page":"185","article-title":"Fast training of support vector machines using sequential minimal optimization","author":"platt","year":"1999","journal-title":"Advances in Kernel Methods – Support Vector Learning"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2011.06.011"},{"key":"ref18","first-page":"41","article-title":"Making large-scale SVM learning practical","author":"joachims","year":"1999","journal-title":"Advances in Kernel Methods – Support Vector Learning"},{"key":"ref19","first-page":"1467","article-title":"Parallel software for training large scale support vector machines on multiprocessor systems","volume":"7","author":"zanni","year":"2006","journal-title":"J Mach Learn Res"},{"article-title":"A review of GPU open source support vector machines training implementations","year":"2017","author":"vanek","key":"ref28"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/JSTARS.2015.2461136"},{"key":"ref27","first-page":"521","article-title":"Parallel support vector machines: The cascade SVM","volume":"17","author":"graf","year":"2004","journal-title":"Proc Advances Neural Inf Process Syst"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.cageo.2012.08.023"},{"key":"ref6","doi-asserted-by":"crossref","DOI":"10.1201\/b10911","author":"liang","year":"2016","journal-title":"Support Vector Machines and Their Application in Chemistry and Biotechnology"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-39384-1_55"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-012-1324-4"},{"key":"ref8","doi-asserted-by":"crossref","first-page":"905","DOI":"10.1109\/TPAMI.2007.1068","article-title":"Twin support vector machines for pattern classification","volume":"29","author":"khemchandani","year":"2007","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"ref7","first-page":"203","article-title":"Optimization techniques for semi-supervised support vector machines","volume":"9","author":"chapelle","year":"2008","journal-title":"J Mach Learn Res"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejor.2017.02.037"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2006.17"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/j.indmarman.2016.08.003"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1162\/089976601300014493"},{"key":"ref22","first-page":"1","article-title":"A parallel training algorithm for large scale support vector machines","author":"yom-tov","year":"2005","journal-title":"Proc Neural Inf Process Syst Workshop Large Scale Kernel Mach"},{"key":"ref21","first-page":"1889","article-title":"Working set selection using second order information for training support vector machines","volume":"6","author":"fan","year":"2005","journal-title":"J Mach Learn Res"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/IPDPS.2014.88"},{"key":"ref24","first-page":"616","article-title":"Multi-threaded support vector machines for pattern recognition","author":"gon\u00e7alves","year":"2012","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/FCCM.2009.34"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.2006.875989"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2005.77"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1080\/10556780500140714"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/IPDPS.2015.117"}],"container-title":["IEEE Transactions on Parallel and Distributed Systems"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/71\/8103836\/07990554.pdf?arnumber=7990554","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,12]],"date-time":"2022-01-12T11:39:28Z","timestamp":1641987568000},"score":1,"resource":{"primary":{"URL":"http:\/\/ieeexplore.ieee.org\/document\/7990554\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,12,1]]},"references-count":43,"journal-issue":{"issue":"12"},"URL":"https:\/\/doi.org\/10.1109\/tpds.2017.2731764","relation":{},"ISSN":["1045-9219"],"issn-type":[{"type":"print","value":"1045-9219"}],"subject":[],"published":{"date-parts":[[2017,12,1]]}}}