{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,24]],"date-time":"2025-07-24T10:54:50Z","timestamp":1753354490084,"version":"3.37.3"},"reference-count":56,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"8","license":[{"start":{"date-parts":[[2023,8,1]],"date-time":"2023-08-01T00:00:00Z","timestamp":1690848000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2023,8,1]],"date-time":"2023-08-01T00:00:00Z","timestamp":1690848000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,8,1]],"date-time":"2023-08-01T00:00:00Z","timestamp":1690848000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001691","name":"Japan Society for the Promotion of Science","doi-asserted-by":"publisher","award":["19H05728"],"award-info":[{"award-number":["19H05728"]}],"id":[{"id":"10.13039\/501100001691","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002241","name":"Japan Science and Technology Agency","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100002241","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Pioneering Research Initiated by Next Generation","award":["JPMJSP2106"],"award-info":[{"award-number":["JPMJSP2106"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U21A20485","61976175"],"award-info":[{"award-number":["U21A20485","61976175"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Biomed. Eng."],"published-print":{"date-parts":[[2023,8]]},"DOI":"10.1109\/tbme.2023.3246599","type":"journal-article","created":{"date-parts":[[2023,4,24]],"date-time":"2023-04-24T18:19:40Z","timestamp":1682360380000},"page":"2416-2429","source":"Crossref","is-referenced-by-count":7,"title":["Correntropy-Based Logistic Regression With Automatic Relevance Determination for Robust Sparse Brain Activity Decoding"],"prefix":"10.1109","volume":"70","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6938-5012","authenticated-orcid":false,"given":"Yuanhao","family":"Li","sequence":"first","affiliation":[{"name":"Institute of Innovative Research, Tokyo Institute of Technology, Yokohama, Japan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1710-3818","authenticated-orcid":false,"given":"Badong","family":"Chen","sequence":"additional","affiliation":[{"name":"Institute of Artificial Intelligence and Robotics, Xi&#x0027;an Jiaotong University, China"}]},{"given":"Yuxi","family":"Shi","sequence":"additional","affiliation":[{"name":"Institute of Innovative Research, Tokyo Institute of Technology, Japan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7495-9113","authenticated-orcid":false,"given":"Natsue","family":"Yoshimura","sequence":"additional","affiliation":[{"name":"Institute of Innovative Research, Tokyo Institute of Technology, Japan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8169-0044","authenticated-orcid":false,"given":"Yasuharu","family":"Koike","sequence":"additional","affiliation":[{"name":"Institute of Innovative Research, Tokyo Institute of Technology, Japan"}]}],"member":"263","reference":[{"key":"ref13","first-page":"1","article-title":"The impact of regularization on high-dimensional logistic regression","volume":"32","author":"salehi","year":"0","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref12","first-page":"11","article-title":"Machine learning techniques for brain-computer interfaces","volume":"49","author":"m\u00fcller","year":"2004","journal-title":"Biomed Tech"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1016\/j.jfranklin.2015.03.039"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1145\/1015330.1015435"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1111\/j.2517-6161.1996.tb02080.x"},{"key":"ref53","doi-asserted-by":"crossref","first-page":"1561","DOI":"10.1109\/TPAMI.2010.220","article-title":"Maximum correntropy criterion for robust face recognition","volume":"33","author":"he","year":"2011","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/TSMC.2018.2855106"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.4135\/9781412983433"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2017.2783364"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2008.11.007"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1162\/NECO_a_00155"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2010.02.040"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2008.05.050"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2008.06.018"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.3389\/fninf.2018.00051"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/TBME.2011.2177523"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1016\/j.jneumeth.2014.10.023"},{"key":"ref46","first-page":"774","article-title":"Robust sparse regression under adversarial corruption","author":"chen","year":"0","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref45","first-page":"1","article-title":"Regularized M-estimators with nonconvexity: Statistical and algorithmic theory for local optima","volume":"26","author":"loh","year":"0","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1016\/S0926-6410(01)00116-1"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1007\/s10462-004-0751-8"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2010.2103949"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2016.2637351"},{"journal-title":"Minimum Error Entropy Classification","year":"2013","author":"s\u00e1","key":"ref44"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.2017.1285773"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1007\/s00062-009-9002-3"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2015.03.051"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuron.2008.11.004"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1016\/j.tics.2006.07.005"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1088\/1741-2560\/3\/4\/007"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.3390\/s19061423"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1038\/nn1444"},{"key":"ref5","first-page":"200","article-title":"Frequency and phase mixed coding in SSVEP-based brain&#x2013;computer interface","volume":"58","author":"jia","year":"2010","journal-title":"IEEE Trans Biomed Eng"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2013.07.017"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2016.09.008"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2009.02.028"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4419-1570-2"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1017\/S0048577200980259"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.3389\/fnins.2016.00175"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2013.12.035"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2021.3082571"},{"key":"ref32","article-title":"Decoding of ankle flexion and extension from cortical current sources estimated from non-invasive brain activity recording methods","volume":"11","author":"tobar","year":"2018","journal-title":"Front Neurosci"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1038\/nrn1931"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/S1388-2457(02)00057-3"},{"key":"ref39","first-page":"993","article-title":"Learning with the maximum correntropy criterion induced losses for regression","volume":"16","author":"feng","year":"2015","journal-title":"J Mach Learn Res"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2007.896065"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0125479"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.3389\/fnsys.2014.00085"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1142\/S0129065721500349"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1126\/sciadv.aaq0183"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2003.1227989"},{"key":"ref22","first-page":"1","article-title":"A new view of automatic relevance determination","volume":"20","author":"wipf","year":"0","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1992.4.3.415"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1038\/ncomms11254"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1126\/science.1212003"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1038\/ncomms15037"}],"container-title":["IEEE Transactions on Biomedical Engineering"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/10\/10185979\/10107426.pdf?arnumber=10107426","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,8,7]],"date-time":"2023-08-07T17:58:55Z","timestamp":1691431135000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10107426\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,8]]},"references-count":56,"journal-issue":{"issue":"8"},"URL":"https:\/\/doi.org\/10.1109\/tbme.2023.3246599","relation":{},"ISSN":["0018-9294","1558-2531"],"issn-type":[{"type":"print","value":"0018-9294"},{"type":"electronic","value":"1558-2531"}],"subject":[],"published":{"date-parts":[[2023,8]]}}}