{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,4]],"date-time":"2026-07-04T17:10:40Z","timestamp":1783185040097,"version":"3.54.6"},"reference-count":36,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"5","license":[{"start":{"date-parts":[[2018,5,1]],"date-time":"2018-05-01T00:00:00Z","timestamp":1525132800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"}],"funder":[{"DOI":"10.13039\/100005156","name":"Alexander von Humboldt Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100005156","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61603248"],"award-info":[{"award-number":["61603248"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000781","name":"ERC AdG A-DATADRIVE-B","doi-asserted-by":"publisher","award":["290923"],"award-info":[{"award-number":["290923"]}],"id":[{"id":"10.13039\/501100000781","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000781","name":"ERC AdG A-DATADRIVE-B","doi-asserted-by":"publisher","award":["KUL: GOA\/10\/09 MaNet"],"award-info":[{"award-number":["KUL: GOA\/10\/09 MaNet"]}],"id":[{"id":"10.13039\/501100000781","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000781","name":"ERC AdG A-DATADRIVE-B","doi-asserted-by":"publisher","award":["CoE PFV\/10\/002(OPTEC)"],"award-info":[{"award-number":["CoE PFV\/10\/002(OPTEC)"]}],"id":[{"id":"10.13039\/501100000781","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000781","name":"ERC AdG A-DATADRIVE-B","doi-asserted-by":"publisher","award":["BIL12\/11T"],"award-info":[{"award-number":["BIL12\/11T"]}],"id":[{"id":"10.13039\/501100000781","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003130","name":"FWO","doi-asserted-by":"publisher","award":["G.0377.12"],"award-info":[{"award-number":["G.0377.12"]}],"id":[{"id":"10.13039\/501100003130","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003130","name":"FWO","doi-asserted-by":"publisher","award":["G.088114N"],"award-info":[{"award-number":["G.088114N"]}],"id":[{"id":"10.13039\/501100003130","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003130","name":"FWO","doi-asserted-by":"publisher","award":["SBO POM (100031)"],"award-info":[{"award-number":["SBO POM (100031)"]}],"id":[{"id":"10.13039\/501100003130","id-type":"DOI","asserted-by":"publisher"}]},{"name":"IUAP P7\/19 DYSCO"},{"DOI":"10.13039\/501100001809","name":"NSFC","doi-asserted-by":"publisher","award":["61134012"],"award-info":[{"award-number":["61134012"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"NSFC","doi-asserted-by":"publisher","award":["61473165"],"award-info":[{"award-number":["61473165"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Neural Netw. Learning Syst."],"published-print":{"date-parts":[[2018,5]]},"DOI":"10.1109\/tnnls.2017.2668610","type":"journal-article","created":{"date-parts":[[2017,3,1]],"date-time":"2017-03-01T19:13:29Z","timestamp":1488395609000},"page":"2025-2030","source":"Crossref","is-referenced-by-count":18,"title":["Classification With Truncated &lt;inline-formula&gt; &lt;tex-math notation=\"LaTeX\"&gt;$\\ell _{1}$ &lt;\/tex-math&gt; &lt;\/inline-formula&gt; Distance Kernel"],"prefix":"10.1109","volume":"29","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4285-6520","authenticated-orcid":false,"given":"Xiaolin","family":"Huang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8846-6352","authenticated-orcid":false,"given":"Johan A. K.","family":"Suykens","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shuning","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joachim","family":"Hornegger","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9550-5284","authenticated-orcid":false,"given":"Andreas","family":"Maier","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref33","article-title":"UCI machine learning repository","author":"frank","year":"2010"},{"key":"ref32","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"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.2008.2000451"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/18.256506"},{"key":"ref36","author":"kampa","year":"2016","journal-title":"Automatic Parameter Selection Integrated Brain Imaging Center UW Medical Center"},{"key":"ref35","article-title":"LS-SVMlab toolbox user&#x2019;s guide, version 1.8","author":"de brabanter","year":"2010"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1145\/1961189.1961199"},{"key":"ref10","article-title":"A study on sigmoid kernels for SVM and the training of non-PSD kernels by SMO-type methods","author":"lin","year":"2003"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1145\/1015330.1015443"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2005.78"},{"key":"ref13","first-page":"953","article-title":"Support vector machine classification with indefinite kernels","author":"luss","year":"2008","journal-title":"Advances in neural information processing systems"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1145\/1390156.1390174"},{"key":"ref15","first-page":"2205","article-title":"Analysis of SVM with indefinite kernels","author":"ying","year":"2009","journal-title":"Advances in neural information processing systems"},{"key":"ref16","first-page":"942","article-title":"Learning SVM classifiers with indefinite kernels","author":"gu","year":"2012","journal-title":"Proc 26th AAAI Conf Artif Intell"},{"key":"ref17","first-page":"32","article-title":"Support vector machines with indefinite kernels","author":"alabdulmohsin","year":"2014","journal-title":"Proc Asian Conf Mach Learn"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2015.2477830"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1162\/NECO_a_00770"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1007\/3-540-46084-5_117"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.2010.2094624"},{"key":"ref27","first-page":"299","article-title":"Classes of kernels for machine learning: A statistics perspective","volume":"2","author":"genton","year":"2002","journal-title":"J Mach Learn Res"},{"key":"ref3","first-page":"1883","article-title":"Fast and scalable local kernel machines","volume":"11","author":"segata","year":"2010","journal-title":"J Mach Learn Res"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2014.09.003"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2007.903900"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2013.01.023"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2012.62"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2008.4587630"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2006.301"},{"key":"ref9","first-page":"175","article-title":"A generalized kernel approach to dissimilarity-based classification","volume":"2","author":"pekalska","year":"2002","journal-title":"J Mach Learn Res"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.1980.4766988"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1016\/j.acha.2016.09.001"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1142\/9789812776655"},{"key":"ref21","author":"vapnik","year":"1998","journal-title":"Statistical Learning Theory"},{"key":"ref24","author":"anselmi","year":"2015","journal-title":"Deep convolutional networks are hierarchical kernel machines"},{"key":"ref23","first-page":"49","article-title":"1-Norm support vector machines","author":"zhu","year":"2004","journal-title":"Advances in neural information processing systems"},{"key":"ref26","doi-asserted-by":"crossref","DOI":"10.1002\/9781119115151","author":"cressie","year":"1993","journal-title":"Statistics for Spatial Data"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/83.846240"}],"container-title":["IEEE Transactions on Neural Networks and Learning Systems"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/5962385\/8338465\/07867066.pdf?arnumber=7867066","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,6,22]],"date-time":"2024-06-22T19:28:18Z","timestamp":1719084498000},"score":1,"resource":{"primary":{"URL":"http:\/\/ieeexplore.ieee.org\/document\/7867066\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,5]]},"references-count":36,"journal-issue":{"issue":"5"},"URL":"https:\/\/doi.org\/10.1109\/tnnls.2017.2668610","relation":{},"ISSN":["2162-237X","2162-2388"],"issn-type":[{"value":"2162-237X","type":"print"},{"value":"2162-2388","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,5]]}}}