{"id":"https://openalex.org/W2584452946","doi":"https://doi.org/10.1109/icmla.2016.0058","title":"Nonlinear Metric Learning for Semi-Supervised Learning via Coherent Point Drifting","display_name":"Nonlinear Metric Learning for Semi-Supervised Learning via Coherent Point Drifting","publication_year":2016,"publication_date":"2016-12-01","ids":{"openalex":"https://openalex.org/W2584452946","doi":"https://doi.org/10.1109/icmla.2016.0058","mag":"2584452946"},"language":"en","primary_location":{"id":"doi:10.1109/icmla.2016.0058","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmla.2016.0058","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 15th IEEE International Conference on Machine Learning and Applications (ICMLA)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5024893578","display_name":"Pin Zhang","orcid":"https://orcid.org/0000-0002-9004-647X"},"institutions":[{"id":"https://openalex.org/I4210105618","display_name":"Alzheimer\u2019s Disease Neuroimaging Initiative","ror":"https://ror.org/01j20wc74","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I4210105618"]},{"id":"https://openalex.org/I4210106879","display_name":"Ohio University","ror":"https://ror.org/01jr3y717","country_code":"US","type":"education","lineage":["https://openalex.org/I4210106879"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Pin Zhang","raw_affiliation_strings":["For the Alzheimer's Disease Neuroimaging Initiative, Ohio University, Athens, OH"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"For the Alzheimer's Disease Neuroimaging Initiative, Ohio University, Athens, OH","institution_ids":["https://openalex.org/I4210105618","https://openalex.org/I4210106879"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049790626","display_name":"Bibo Shi","orcid":"https://orcid.org/0000-0002-9918-0448"},"institutions":[{"id":"https://openalex.org/I170897317","display_name":"Duke University","ror":"https://ror.org/00py81415","country_code":"US","type":"education","lineage":["https://openalex.org/I170897317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bibo Shi","raw_affiliation_strings":["Department of Radiology, Duke University, Durhan, NC"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Radiology, Duke University, Durhan, NC","institution_ids":["https://openalex.org/I170897317"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5106634125","display_name":"Charles D. Smith","orcid":null},"institutions":[{"id":"https://openalex.org/I143302722","display_name":"University of Kentucky","ror":"https://ror.org/02k3smh20","country_code":"US","type":"education","lineage":["https://openalex.org/I143302722"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Charles D. Smith","raw_affiliation_strings":["Department of Neurology, University of Kentucky, Lexinton, KY"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Neurology, University of Kentucky, Lexinton, KY","institution_ids":["https://openalex.org/I143302722"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102756615","display_name":"Jundong Liu","orcid":"https://orcid.org/0000-0002-9049-2832"},"institutions":[{"id":"https://openalex.org/I4210106879","display_name":"Ohio University","ror":"https://ror.org/01jr3y717","country_code":"US","type":"education","lineage":["https://openalex.org/I4210106879"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jundong Liu","raw_affiliation_strings":["Ohio University, Athens, OH, US"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ohio University, Athens, OH, US","institution_ids":["https://openalex.org/I4210106879"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"16","issue":null,"first_page":"314","last_page":"319"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9991000294685364,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9991000294685364,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9980999827384949,"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/T10057","display_name":"Face and Expression Recognition","score":0.996999979019165,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.7262735962867737},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.6627342104911804},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5869393348693848},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5813717842102051},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.5377943515777588},{"id":"https://openalex.org/keywords/transformation","display_name":"Transformation (genetics)","score":0.4954334497451782},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.4763220250606537},{"id":"https://openalex.org/keywords/metric-space","display_name":"Metric space","score":0.45575350522994995},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.44309112429618835},{"id":"https://openalex.org/keywords/laplace-operator","display_name":"Laplace operator","score":0.437078595161438},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3920244872570038},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38366252183914185},{"id":"https://openalex.org/keywords/topology","display_name":"Topology (electrical circuits)","score":0.32220911979675293},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2751719653606415},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.08029967546463013}],"concepts":[{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.7262735962867737},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.6627342104911804},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5869393348693848},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5813717842102051},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.5377943515777588},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.4954334497451782},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.4763220250606537},{"id":"https://openalex.org/C198043062","wikidata":"https://www.wikidata.org/wiki/Q180953","display_name":"Metric space","level":2,"score":0.45575350522994995},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.44309112429618835},{"id":"https://openalex.org/C165700671","wikidata":"https://www.wikidata.org/wiki/Q203484","display_name":"Laplace operator","level":2,"score":0.437078595161438},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3920244872570038},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38366252183914185},{"id":"https://openalex.org/C184720557","wikidata":"https://www.wikidata.org/wiki/Q7825049","display_name":"Topology (electrical circuits)","level":2,"score":0.32220911979675293},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2751719653606415},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.08029967546463013},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icmla.2016.0058","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmla.2016.0058","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 15th IEEE International Conference on Machine Learning and Applications (ICMLA)","raw_type":"proceedings-article"},{"id":"mag:2748356665","is_oa":false,"landing_page_url":"http://jglobal.jst.go.jp/en/public/201702228287429119","pdf_url":null,"source":{"id":"https://openalex.org/S4306512817","display_name":"IEEE Conference Proceedings","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":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":"IEEE Conference Proceedings","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1854772995","https://openalex.org/W1966949944","https://openalex.org/W1977193486","https://openalex.org/W1980781669","https://openalex.org/W1995277044","https://openalex.org/W2019337445","https://openalex.org/W2057463961","https://openalex.org/W2093602450","https://openalex.org/W2097089247","https://openalex.org/W2107229253","https://openalex.org/W2109501666","https://openalex.org/W2124789966","https://openalex.org/W2134236847","https://openalex.org/W2151624282","https://openalex.org/W2152756885","https://openalex.org/W2157911873","https://openalex.org/W2170780515","https://openalex.org/W2296748895","https://openalex.org/W2322322926","https://openalex.org/W2525655278","https://openalex.org/W2950690897","https://openalex.org/W6638989246","https://openalex.org/W6645510500","https://openalex.org/W6678280165","https://openalex.org/W6682811751","https://openalex.org/W6727819878"],"related_works":["https://openalex.org/W2353644209","https://openalex.org/W4280529579","https://openalex.org/W2593663830","https://openalex.org/W2348743188","https://openalex.org/W2902317490","https://openalex.org/W2463239216","https://openalex.org/W4387423451","https://openalex.org/W2025460258","https://openalex.org/W2056619254","https://openalex.org/W2046628353"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3],"propose":[4],"a":[5,30],"nonlinear":[6,32],"metric":[7,103],"learning":[8,16,104],"framework":[9,70],"to":[10],"boost":[11],"the":[12,26,38,52,56,95,101],"performance":[13],"of":[14,22,58,97],"semi-supervised":[15],"(SSL)":[17],"algorithms.":[18],"Constructed":[19],"on":[20,88],"top":[21],"Laplacian":[23],"SVM":[24],"(LapSVM),":[25],"proposed":[27],"method":[28],"learns":[29],"smooth":[31,67],"feature":[33],"space":[34],"transformation":[35],"that":[36],"makes":[37],"input":[39],"data":[40],"points":[41],"more":[42],"linearly":[43],"separable.":[44],"Coherent":[45],"point":[46],"drifting":[47],"(CPD)":[48],"is":[49],"utilized":[50],"as":[51],"geometric":[53],"model":[54],"with":[55,79],"consideration":[57],"its":[59],"remarkable":[60],"expressive":[61],"power":[62],"in":[63,106],"generating":[64],"sophisticated":[65],"yet":[66],"deformations.":[68],"Our":[69],"has":[71],"broad":[72],"applicability,":[73],"and":[74,90],"it":[75],"can":[76],"be":[77],"integrated":[78],"many":[80],"other":[81],"SSL":[82],"classifiers":[83],"than":[84],"LapSVM.":[85],"Experiments":[86],"performed":[87],"synthetic":[89],"real":[91],"world":[92],"datasets":[93],"show":[94],"effectiveness":[96],"our":[98],"CPD-LapSVM":[99],"over":[100],"state-of-the-art":[102],"solutions":[105],"SSL.":[107]},"counts_by_year":[{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":3}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}