{"id":"https://openalex.org/W2988440681","doi":"https://doi.org/10.3390/e21111125","title":"Sub-Graph Regularization on Kernel Regression for Robust Semi-Supervised Dimensionality Reduction","display_name":"Sub-Graph Regularization on Kernel Regression for Robust Semi-Supervised Dimensionality Reduction","publication_year":2019,"publication_date":"2019-11-15","ids":{"openalex":"https://openalex.org/W2988440681","doi":"https://doi.org/10.3390/e21111125","mag":"2988440681"},"language":"en","primary_location":{"id":"doi:10.3390/e21111125","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e21111125","pdf_url":"https://www.mdpi.com/1099-4300/21/11/1125/pdf?version=1574328058","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1099-4300/21/11/1125/pdf?version=1574328058","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5086736724","display_name":"Jiao Liu","orcid":"https://orcid.org/0000-0001-9931-6918"},"institutions":[{"id":"https://openalex.org/I141962983","display_name":"Shanghai University of Engineering Science","ror":"https://ror.org/0557b9y08","country_code":"CN","type":"education","lineage":["https://openalex.org/I141962983"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiao Liu","raw_affiliation_strings":["School of Management Studies, Shanghai University of Engineering Science, Shanghai 201600, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Management Studies, Shanghai University of Engineering Science, Shanghai 201600, China","institution_ids":["https://openalex.org/I141962983"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061195038","display_name":"Mingbo Zhao","orcid":"https://orcid.org/0000-0003-0381-4360"},"institutions":[{"id":"https://openalex.org/I181326427","display_name":"Donghua University","ror":"https://ror.org/035psfh38","country_code":"CN","type":"education","lineage":["https://openalex.org/I181326427"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Mingbo Zhao","raw_affiliation_strings":["School of Information Science and Technology, Donghua University, Shanghai 201620, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, Donghua University, Shanghai 201620, China","institution_ids":["https://openalex.org/I181326427"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102903128","display_name":"Weijian Kong","orcid":"https://orcid.org/0000-0001-9030-8778"},"institutions":[{"id":"https://openalex.org/I181326427","display_name":"Donghua University","ror":"https://ror.org/035psfh38","country_code":"CN","type":"education","lineage":["https://openalex.org/I181326427"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Weijian Kong","raw_affiliation_strings":["School of Information Science and Technology, Donghua University, Shanghai 201620, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, Donghua University, Shanghai 201620, China","institution_ids":["https://openalex.org/I181326427"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5061195038","https://openalex.org/A5102903128"],"corresponding_institution_ids":["https://openalex.org/I181326427"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2165},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2165},"fwci":0.0,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.13145414,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"21","issue":"11","first_page":"1125","last_page":"1125"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.991599977016449,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":0.9847000241279602,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.8266040086746216},{"id":"https://openalex.org/keywords/semi-supervised-learning","display_name":"Semi-supervised learning","score":0.6456321477890015},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6109620332717896},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5907683372497559},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.5703887939453125},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.5491084456443787},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.5384547114372253},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5044318437576294},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5015652179718018},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.4794134795665741},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4639071822166443},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.4526403546333313},{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.4467422068119049},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4193488359451294},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3217427730560303},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.13987863063812256},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.08861202001571655}],"concepts":[{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.8266040086746216},{"id":"https://openalex.org/C58973888","wikidata":"https://www.wikidata.org/wiki/Q1041418","display_name":"Semi-supervised learning","level":2,"score":0.6456321477890015},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6109620332717896},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5907683372497559},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.5703887939453125},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.5491084456443787},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.5384547114372253},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5044318437576294},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5015652179718018},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.4794134795665741},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4639071822166443},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.4526403546333313},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.4467422068119049},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4193488359451294},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3217427730560303},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.13987863063812256},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.08861202001571655},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.3390/e21111125","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e21111125","pdf_url":"https://www.mdpi.com/1099-4300/21/11/1125/pdf?version=1574328058","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:4b20feb24a854319bcc417f92b5639da","is_oa":true,"landing_page_url":"https://doaj.org/article/4b20feb24a854319bcc417f92b5639da","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy, Vol 21, Iss 11, p 1125 (2019)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1099-4300/21/11/1125/","is_oa":true,"landing_page_url":"http://dx.doi.org/10.3390/e21111125","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:7514469","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/7514469","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy (Basel)","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/e21111125","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e21111125","pdf_url":"https://www.mdpi.com/1099-4300/21/11/1125/pdf?version=1574328058","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.7300000190734863}],"awards":[{"id":"https://openalex.org/G6158442140","display_name":null,"funder_award_id":"61971121, 61601112","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W745184511","https://openalex.org/W1500351990","https://openalex.org/W1933573347","https://openalex.org/W1969198379","https://openalex.org/W1978372964","https://openalex.org/W1993603321","https://openalex.org/W2001141328","https://openalex.org/W2006793117","https://openalex.org/W2010379776","https://openalex.org/W2019863495","https://openalex.org/W2026731079","https://openalex.org/W2035331133","https://openalex.org/W2053186076","https://openalex.org/W2100659887","https://openalex.org/W2104290444","https://openalex.org/W2104990616","https://openalex.org/W2111371772","https://openalex.org/W2112074816","https://openalex.org/W2117553576","https://openalex.org/W2123921160","https://openalex.org/W2132709984","https://openalex.org/W2133442079","https://openalex.org/W2139823104","https://openalex.org/W2154455818","https://openalex.org/W2156338447","https://openalex.org/W2163584563","https://openalex.org/W2167665791","https://openalex.org/W2319358180","https://openalex.org/W2520742745","https://openalex.org/W2573426660","https://openalex.org/W2740578684","https://openalex.org/W2761726598","https://openalex.org/W2894889024","https://openalex.org/W2942602355","https://openalex.org/W2963174546","https://openalex.org/W2964281014","https://openalex.org/W2964492019","https://openalex.org/W3104635321","https://openalex.org/W6682494755"],"related_works":["https://openalex.org/W2114217318","https://openalex.org/W2794812819","https://openalex.org/W2587881214","https://openalex.org/W3104072235","https://openalex.org/W3036945320","https://openalex.org/W2370263288","https://openalex.org/W1995622179","https://openalex.org/W1484111231","https://openalex.org/W2169311637","https://openalex.org/W3192451249"],"abstract_inverted_index":{"Dimensionality":[0],"reduction":[1,22],"has":[2],"always":[3],"been":[4],"a":[5,58,71],"major":[6],"problem":[7],"for":[8,81,158],"handling":[9],"huge":[10],"dimensionality":[11,21,82,141],"datasets.":[12],"Due":[13],"to":[14,47,94,99],"the":[15,86,96,118,125,132,152,156,159],"utilization":[16],"of":[17,122,135],"labeled":[18,43,64],"data,":[19],"supervised":[20,39],"methods":[23,40,55],"such":[24],"as":[25],"Linear":[26],"Discriminant":[27],"Analysis":[28],"tend":[29],"achieve":[30,48,140],"better":[31],"classification":[32],"performance":[33],"compared":[34],"with":[35],"unsupervised":[36],"methods.":[37],"However,":[38,102],"need":[41],"sufficient":[42],"data":[44,137],"in":[45],"order":[46],"satisfying":[49],"results.":[50],"Therefore,":[51,124],"semi-supervised":[52,91],"learning":[53,92],"(SSL)":[54],"can":[56,128],"be":[57],"practical":[59],"selection":[60],"rather":[61],"than":[62],"utilizing":[63],"data.":[65,101],"In":[66,84],"this":[67],"paper,":[68],"we":[69],"develop":[70],"novel":[72],"SSL":[73],"method":[74,93,127],"by":[75,113],"extending":[76],"anchor":[77],"graph":[78],"regularization":[79],"(AGR)":[80],"reduction.":[83,142],"detail,":[85],"AGR":[87,112],"is":[88],"an":[89],"accelerating":[90],"propagate":[95],"class":[97,133],"labels":[98,134],"unlabeled":[100,136],"it":[103],"cannot":[104],"handle":[105],"new":[106],"incoming":[107],"samples.":[108],"We":[109],"thereby":[110],"improve":[111],"adding":[114],"kernel":[115],"regression":[116],"on":[117,145],"basic":[119],"objective":[120],"function":[121],"AGR.":[123],"proposed":[126,160],"not":[129],"only":[130],"estimate":[131],"but":[138],"also":[139],"Extensive":[143],"simulations":[144],"several":[146],"benchmark":[147],"datasets":[148],"are":[149],"conducted,":[150],"and":[151],"simulation":[153],"results":[154],"verify":[155],"effectiveness":[157],"work.":[161]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
