{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2023,9,13]],"date-time":"2023-09-13T21:18:45Z","timestamp":1694639925937},"reference-count":17,"publisher":"Informa UK Limited","issue":"7","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Communications in Statistics - Simulation and Computation"],"published-print":{"date-parts":[[2010,7,30]]},"DOI":"10.1080\/03610911003699901","type":"journal-article","created":{"date-parts":[[2010,7,29]],"date-time":"2010-07-29T13:25:44Z","timestamp":1280409944000},"page":"1485-1498","source":"Crossref","is-referenced-by-count":2,"title":["Learning Low-Rank Kernel Matrices with Column-Based Methods"],"prefix":"10.1080","volume":"39","author":[{"given":"Songhua","family":"Liu","sequence":"first","affiliation":[]},{"given":"Junying","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Keguo","family":"Sun","sequence":"additional","affiliation":[]}],"member":"301","published-online":{"date-parts":[[2010,7,27]]},"reference":[{"key":"CIT0001","doi-asserted-by":"crossref","unstructured":"Bach , F. R. Jordan , M. I. ( 2005 ). Predictive low-rank decomposition for kernel methods.Proc. 22nd International Conference on Machine Learning, 7\u201311 August, 2005. Germany: Bonn , pp. 33 \u2013 40 .","DOI":"10.1145\/1102351.1102356"},{"key":"CIT0002","doi-asserted-by":"crossref","first-page":"2385","DOI":"10.1162\/089976600300014980","volume":"12","author":"Baudat G.","year":"2000","journal-title":"Neural Computation"},{"key":"CIT0003","doi-asserted-by":"crossref","first-page":"369","DOI":"10.1073\/pnas.0810600105","volume":"106","author":"Belabbas M.-A.","year":"2009","journal-title":"Proceedings of the National Academy of Sciences USA"},{"key":"CIT0004","doi-asserted-by":"crossref","unstructured":"Boutsidis , C. Mahoney , M. W. Drineas , P. ( 2009 ). An improved approximation algorithm for the column subset selection problem.Proc. 20th Annual SODA.New York, 4\u20136 Januray, 2009, pp. 968\u2013977 .","DOI":"10.1137\/1.9781611973068.105"},{"key":"CIT0005","first-page":"1875","volume":"9","author":"Braun M. L.","year":"2008","journal-title":"J. Comput. Math."},{"key":"CIT0006","first-page":"2153","volume":"6","author":"Drineas P.","year":"2005","journal-title":"Journal of Computational Mathematics"},{"key":"CIT0007","first-page":"243","volume":"2","author":"Fine S.","year":"2001","journal-title":"Journal of Computational Mathematics"},{"key":"CIT0008","volume-title":"Matrix Computations.","author":"Golub G. H.","year":"1996","edition":"3"},{"issue":"1","key":"CIT0009","doi-asserted-by":"crossref","first-page":"143","DOI":"10.1081\/SAC-100001864","volume":"30","author":"Kitchin P. L.","year":"2001","journal-title":"Communications in Statistics\u2014Simulation and Computation"},{"issue":"4","key":"CIT0010","doi-asserted-by":"crossref","first-page":"807","DOI":"10.1080\/03610910701419695","volume":"36","author":"Kozak M.","year":"2007","journal-title":"Communications in Statistics\u2014Simulation and Computation"},{"key":"CIT0011","first-page":"341","volume":"10","author":"Kulis B.","year":"2009","journal-title":"Journal of Computational Mathematics"},{"key":"CIT0012","first-page":"27","volume":"5","author":"Lanckriet G.","year":"2004","journal-title":"Journal of Machine Learning"},{"key":"CIT0013","doi-asserted-by":"crossref","first-page":"1299","DOI":"10.1162\/089976698300017467","volume":"10","author":"Sch\u00f6lkopf B.","year":"1998","journal-title":"Neural Computation"},{"key":"CIT0014","unstructured":"Smola , A. J. Sch\u00f6lkopf , B. (2000). Sparse greedy matrix approximation for machine learning.Proc. 17th International Conference on Machine Learning.29 June\u20132 July, 2000. CA: Stanford, pp. 911\u2013918."},{"key":"CIT0015","first-page":"1415","volume":"3","author":"Torkkola K.","year":"2003","journal-title":"Journal of Machine Learning"},{"issue":"2","key":"CIT0016","doi-asserted-by":"crossref","first-page":"409","DOI":"10.1080\/03610910701792554","volume":"37","author":"Van Sanden S.","year":"2008","journal-title":"Communications in Statistics\u2014Simulation and Computation"},{"key":"CIT0017","unstructured":"Williams , C. K. I. Seeger , M. ( 2001 ). Using the Nystr\u00f6m method to speed up kernel machines. In:Advances in Neural Information Processing Systems.Vancouver, BC, Canada: MIT Press , pp. 682 \u2013 688 ."}],"container-title":["Communications in Statistics - Simulation and Computation"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/www.tandfonline.com\/doi\/pdf\/10.1080\/03610911003699901","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,11,2]],"date-time":"2021-11-02T09:53:59Z","timestamp":1635846839000},"score":1,"resource":{"primary":{"URL":"http:\/\/www.tandfonline.com\/doi\/abs\/10.1080\/03610911003699901"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2010,7,27]]},"references-count":17,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2010,7,27]]},"published-print":{"date-parts":[[2010,7,30]]}},"alternative-id":["10.1080\/03610911003699901"],"URL":"https:\/\/doi.org\/10.1080\/03610911003699901","relation":{},"ISSN":["0361-0918","1532-4141"],"issn-type":[{"value":"0361-0918","type":"print"},{"value":"1532-4141","type":"electronic"}],"subject":[],"published":{"date-parts":[[2010,7,27]]}}}