{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,30]],"date-time":"2024-10-30T07:13:28Z","timestamp":1730272408592,"version":"3.28.0"},"reference-count":25,"publisher":"IEEE","license":[{"start":{"date-parts":[[2020,10,1]],"date-time":"2020-10-01T00:00:00Z","timestamp":1601510400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2020,10,1]],"date-time":"2020-10-01T00:00:00Z","timestamp":1601510400000},"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":[[2020,10]]},"DOI":"10.1109\/iscas45731.2020.9181116","type":"proceedings-article","created":{"date-parts":[[2020,9,29]],"date-time":"2020-09-29T09:22:27Z","timestamp":1601371347000},"page":"1-5","source":"Crossref","is-referenced-by-count":2,"title":["Kernel Least Mean Square Based on the Sparse Nystr\u00f6m Method"],"prefix":"10.1109","author":[{"given":"Haonan","family":"Zhang","sequence":"first","affiliation":[{"name":"Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing, College of Electronic and Information Engineering, Southwest University, Chongqing 400715, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Han","family":"Jiang","sequence":"additional","affiliation":[{"name":"Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing, College of Electronic and Information Engineering, Southwest University, Chongqing 400715, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shiyuan","family":"Wang","sequence":"additional","affiliation":[{"name":"Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing, College of Electronic and Information Engineering, Southwest University, Chongqing 400715, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1991.3.2.213"},{"key":"ref11","doi-asserted-by":"crossref","first-page":"1950","DOI":"10.1109\/TNET.2012.2187923","article-title":"An information theoretic approach of designing sparse kernel adaptive filters","volume":"20","author":"liu","year":"2009","journal-title":"IEEE Trans Neural Netw"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2011.2178446"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2017.2752695"},{"key":"ref14","first-page":"1177","article-title":"Random features for large-scale kernel machines","volume":"20","author":"rahimi","year":"2007","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/MLSP.2012.6349811"},{"key":"ref16","first-page":"682","article-title":"Using the Nyström method to speed up kernel machines","author":"williams","year":"2001","journal-title":"Proc 14th Annu Conf Neural Inf Process Syst"},{"key":"ref17","first-page":"2153","article-title":"On the Nyström method for approxi- mating a Gram matrix for improved kernel-based learning","volume":"6","author":"drineas","year":"2005","journal-title":"J Mach Learn Res"},{"key":"ref18","first-page":"485","article-title":"Nyström method vs random Fourier features: A theoretical and Empirical Comparison","author":"yang","year":"2012","journal-title":"Advances in Neural Information Processing Systems (NIPS)"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1007\/s00034-018-1006-2"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1002\/9780470608593"},{"journal-title":"Machine Learning","year":"1997","author":"mitchell","key":"ref3"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1155\/2008\/784292"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2007.907881"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2004.830985"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TCSII.2013.2281712"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/81.933330"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TCSI.2018.2819655"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.2003.810597"},{"key":"ref20","first-page":"243c264","article-title":"Efficient SVM training using low-rank kernel representations","volume":"2","author":"fine","year":"2001","journal-title":"J Mach Learn Res"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2018.10.064"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1145\/1102351.1102356"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.2010.2064786"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.0810600105"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2002.1017616"}],"event":{"name":"2020 IEEE International Symposium on Circuits and Systems (ISCAS)","start":{"date-parts":[[2020,10,12]]},"location":"Seville, Spain","end":{"date-parts":[[2020,10,14]]}},"container-title":["2020 IEEE International Symposium on Circuits and Systems (ISCAS)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9179985\/9180369\/09181116.pdf?arnumber=9181116","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,15]],"date-time":"2024-01-15T16:08:00Z","timestamp":1705334880000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9181116\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,10]]},"references-count":25,"URL":"https:\/\/doi.org\/10.1109\/iscas45731.2020.9181116","relation":{},"subject":[],"published":{"date-parts":[[2020,10]]}}}