{"id":"https://openalex.org/W2050067514","doi":"https://doi.org/10.1109/ijcnn.2012.6252838","title":"Extracting the informative constraints for semi-supervised marginal projections in multimodal dimensionality reduction","display_name":"Extracting the informative constraints for semi-supervised marginal projections in multimodal dimensionality reduction","publication_year":2012,"publication_date":"2012-06-01","ids":{"openalex":"https://openalex.org/W2050067514","doi":"https://doi.org/10.1109/ijcnn.2012.6252838","mag":"2050067514"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2012.6252838","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2012.6252838","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 2012 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"article","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/A5100423029","display_name":"Zhao Zhang","orcid":"https://orcid.org/0000-0002-5703-7969"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":true,"raw_author_name":"Zhao Zhang","raw_affiliation_strings":["Department of Electronic Engineering, City University of Hong Kong, Kowloon, Hong Kong, China","Department of Electronic Engineering; City University of Hong Kong; Tat Chee Avenue, Kowloon; Hong Kong"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, City University of Hong Kong, Kowloon, Hong Kong, China","institution_ids":["https://openalex.org/I168719708"]},{"raw_affiliation_string":"Department of Electronic Engineering; City University of Hong Kong; Tat Chee Avenue, Kowloon; Hong Kong","institution_ids":["https://openalex.org/I168719708"]}]},{"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/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Mingbo Zhao","raw_affiliation_strings":["Department of Electronic Engineering, City University of Hong Kong, Kowloon, Hong Kong, China","Department of Electronic Engineering; City University of Hong Kong; Tat Chee Avenue, Kowloon; Hong Kong"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, City University of Hong Kong, Kowloon, Hong Kong, China","institution_ids":["https://openalex.org/I168719708"]},{"raw_affiliation_string":"Department of Electronic Engineering; City University of Hong Kong; Tat Chee Avenue, Kowloon; Hong Kong","institution_ids":["https://openalex.org/I168719708"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050716572","display_name":"Tommy W. S. Chow","orcid":"https://orcid.org/0000-0001-7051-0434"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Tommy W. S. Chow","raw_affiliation_strings":["Department of Electronic Engineering, City University of Hong Kong, Kowloon, Hong Kong, China","Department of Electronic Engineering; City University of Hong Kong; Tat Chee Avenue, Kowloon; Hong Kong"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, City University of Hong Kong, Kowloon, Hong Kong, China","institution_ids":["https://openalex.org/I168719708"]},{"raw_affiliation_string":"Department of Electronic Engineering; City University of Hong Kong; Tat Chee Avenue, Kowloon; Hong Kong","institution_ids":["https://openalex.org/I168719708"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100423029"],"corresponding_institution_ids":["https://openalex.org/I168719708"],"apc_list":null,"apc_paid":null,"fwci":0.2745,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.57429214,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"20","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9835000038146973,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9835000038146973,"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":0.9793999791145325,"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":0.9789000153541565,"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/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.7047775983810425},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6389463543891907},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5885658264160156},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4915378987789154},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.48728811740875244},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.4675554037094116},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.42793920636177063},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.42308998107910156},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.4206574559211731},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.4126870930194855},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.388620525598526},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3366779088973999},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2768741846084595},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.2148178219795227}],"concepts":[{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.7047775983810425},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6389463543891907},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5885658264160156},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4915378987789154},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.48728811740875244},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.4675554037094116},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.42793920636177063},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.42308998107910156},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.4206574559211731},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.4126870930194855},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.388620525598526},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3366779088973999},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2768741846084595},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2148178219795227},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","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/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2012.6252838","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2012.6252838","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 2012 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.699999988079071,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1479807131","https://openalex.org/W1510147702","https://openalex.org/W1564277727","https://openalex.org/W1969204685","https://openalex.org/W1984929054","https://openalex.org/W2080322700","https://openalex.org/W2088900896","https://openalex.org/W2095705137","https://openalex.org/W2097308346","https://openalex.org/W2098089028","https://openalex.org/W2100495367","https://openalex.org/W2102708620","https://openalex.org/W2105055468","https://openalex.org/W2109531142","https://openalex.org/W2113739199","https://openalex.org/W2117154949","https://openalex.org/W2117553576","https://openalex.org/W2127177049","https://openalex.org/W2134262590","https://openalex.org/W2135643717","https://openalex.org/W2159832601","https://openalex.org/W2163584563","https://openalex.org/W3014771378","https://openalex.org/W6676189307","https://openalex.org/W6676895082","https://openalex.org/W6677328822","https://openalex.org/W6677524102"],"related_works":["https://openalex.org/W1995622179","https://openalex.org/W4391160746","https://openalex.org/W1484111231","https://openalex.org/W1552543208","https://openalex.org/W2074396517","https://openalex.org/W2166963679","https://openalex.org/W2187269125","https://openalex.org/W1641615907","https://openalex.org/W3089231081","https://openalex.org/W2093956241"],"abstract_inverted_index":{"This":[0],"paper":[1],"discusses":[2],"the":[3,35,41,49,65,77,82,92,109,118,134],"semi-supervised":[4,23,136,172],"marginal":[5,24,119],"projection":[6],"problems":[7],"learning":[8,93],"from":[9],"partial":[10],"constrained":[11],"data.":[12],"Two":[13],"effective":[14,102],"multimodal":[15],"dimensionality":[16],"reduction":[17],"(DR)":[18],"algorithms,":[19],"which":[20],"we":[21],"call":[22],"projections":[25,120],"(SSMP)":[26],"and":[27,60,87,103,133,150],"orthogonal":[28],"SSMP":[29,67],"(OSSMP),":[30],"are":[31,138,152,161],"proposed.":[32],"By":[33],"specifying":[34],"types":[36],"of":[37,52,95,106,117,143,163],"similarity":[38],"pairs":[39],"with":[40,167],"pairwise":[42],"constraints":[43,84,89,111],"(PC),":[44],"our":[45,144,159],"techniques":[46],"can":[47,121],"preserve":[48],"global":[50],"structures":[51,62],"all":[53,76],"points":[54],"as":[55,57],"well":[56],"local":[58],"geometrical":[59],"discriminant":[61],"embedded":[63],"in":[64,68,75],"PC.":[66],"singular":[69],"case":[70],"is":[71,85],"also":[72,99,139],"discussed.":[73],"Because":[74],"PC":[78],"guided":[79],"methods,":[80],"extracting":[81],"informative":[83,110,146],"difficult":[86],"random":[88],"greatly":[90],"affect":[91],"performance":[94],"techniques,":[96],"this":[97,130],"work":[98,132],"presents":[100],"an":[101],"efficient":[104],"methodology":[105],"optimally":[107],"selecting":[108],"for":[112],"learning.":[113],"The":[114,127,141],"analytic":[115],"form":[116],"be":[122],"effectively":[123],"obtained":[124],"by":[125,154],"eigen-decomposition.":[126],"connections":[128],"between":[129],"present":[131],"related":[135],"algorithms":[137,151],"detailed.":[140],"effectiveness":[142],"proposed":[145],"constraint":[147],"selection":[148],"method":[149],"evaluated":[153],"benchmark":[155],"problems.":[156],"Results":[157],"show":[158],"methods":[160],"capable":[162],"delivering":[164],"competitive":[165],"results":[166],"some":[168],"widely":[169],"used":[170],"state-of-the-art":[171],"algorithms.":[173]},"counts_by_year":[{"year":2012,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}