{"id":"https://openalex.org/W2366902341","doi":"https://doi.org/10.1145/2939672.2939811","title":"Collaborative Multi-View Denoising","display_name":"Collaborative Multi-View Denoising","publication_year":2016,"publication_date":"2016-08-08","ids":{"openalex":"https://openalex.org/W2366902341","doi":"https://doi.org/10.1145/2939672.2939811","mag":"2366902341"},"language":"en","primary_location":{"id":"doi:10.1145/2939672.2939811","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2939672.2939811","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining","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/A5100433899","display_name":"Lei Zhang","orcid":"https://orcid.org/0000-0002-2078-4215"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Zhang","raw_affiliation_strings":["Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010150000","display_name":"Shupeng Wang","orcid":"https://orcid.org/0000-0002-2799-4100"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shupeng Wang","raw_affiliation_strings":["Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100419434","display_name":"Xiaoyu Zhang","orcid":"https://orcid.org/0000-0003-1630-6058"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoyu Zhang","raw_affiliation_strings":["Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009822141","display_name":"Yong Wang","orcid":"https://orcid.org/0000-0003-1100-697X"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yong Wang","raw_affiliation_strings":["Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100406156","display_name":"Binbin Li","orcid":"https://orcid.org/0000-0001-5073-7746"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Binbin Li","raw_affiliation_strings":["Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000937401","display_name":"Dinggang Shen","orcid":"https://orcid.org/0000-0002-7934-5698"},"institutions":[{"id":"https://openalex.org/I114027177","display_name":"University of North Carolina at Chapel Hill","ror":"https://ror.org/0130frc33","country_code":"US","type":"education","lineage":["https://openalex.org/I114027177"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dinggang Shen","raw_affiliation_strings":["University of North Carolina, Chapel Hill, NC, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of North Carolina, Chapel Hill, NC, USA","institution_ids":["https://openalex.org/I114027177"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5052278550","display_name":"Shuiwang Ji","orcid":"https://orcid.org/0000-0002-4205-4563"},"institutions":[{"id":"https://openalex.org/I72951846","display_name":"Washington State University","ror":"https://ror.org/05dk0ce17","country_code":"US","type":"education","lineage":["https://openalex.org/I72951846"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shuiwang Ji","raw_affiliation_strings":["Washington State University, Pullman, WA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Washington State University, Pullman, WA, USA","institution_ids":["https://openalex.org/I72951846"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2045","last_page":"2054"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9983000159263611,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9983000159263611,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9915000200271606,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9894999861717224,"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/computer-science","display_name":"Computer science","score":0.7109100222587585},{"id":"https://openalex.org/keywords/complementarity","display_name":"Complementarity (molecular biology)","score":0.5490007996559143},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5472885370254517},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.5417305827140808},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.5140234231948853},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.4887787997722626},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38090085983276367},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3246486783027649}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7109100222587585},{"id":"https://openalex.org/C202269582","wikidata":"https://www.wikidata.org/wiki/Q2644277","display_name":"Complementarity (molecular biology)","level":2,"score":0.5490007996559143},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5472885370254517},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.5417305827140808},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.5140234231948853},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.4887787997722626},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38090085983276367},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3246486783027649},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2939672.2939811","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2939672.2939811","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3182301627","display_name":null,"funder_award_id":"DBI-1147134","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4316741816","display_name":null,"funder_award_id":"DBI-1350258","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W612386257","https://openalex.org/W1523385540","https://openalex.org/W1566499617","https://openalex.org/W1576520375","https://openalex.org/W1871180460","https://openalex.org/W1963631516","https://openalex.org/W1981613567","https://openalex.org/W1984983329","https://openalex.org/W1998635907","https://openalex.org/W2001619934","https://openalex.org/W2048679005","https://openalex.org/W2054540100","https://openalex.org/W2071207147","https://openalex.org/W2076365336","https://openalex.org/W2081863860","https://openalex.org/W2084812512","https://openalex.org/W2086953401","https://openalex.org/W2091449379","https://openalex.org/W2100235303","https://openalex.org/W2104606180","https://openalex.org/W2106053110","https://openalex.org/W2106277773","https://openalex.org/W2109824782","https://openalex.org/W2117513046","https://openalex.org/W2118550318","https://openalex.org/W2122111042","https://openalex.org/W2124541940","https://openalex.org/W2132610780","https://openalex.org/W2134332047","https://openalex.org/W2144935315","https://openalex.org/W2151532250","https://openalex.org/W2154624311","https://openalex.org/W2167732364","https://openalex.org/W2169495281","https://openalex.org/W2179647599","https://openalex.org/W2611328865","https://openalex.org/W2798141208","https://openalex.org/W3141595720","https://openalex.org/W6628968817","https://openalex.org/W6631216910","https://openalex.org/W6675436802","https://openalex.org/W6680962578"],"related_works":["https://openalex.org/W2521519254","https://openalex.org/W3139833644","https://openalex.org/W3123110765","https://openalex.org/W4383553409","https://openalex.org/W2212953222","https://openalex.org/W2104948296","https://openalex.org/W1735800226","https://openalex.org/W4285172739","https://openalex.org/W3123208392","https://openalex.org/W3209466624"],"abstract_inverted_index":{"In":[0],"multi-view":[1,56,76,138],"learning":[2],"applications,":[3],"like":[4],"multimedia":[5],"analysis":[6],"and":[7,32,66,110,129,158,175,197],"information":[8,149],"retrieval,":[9],"we":[10,90,161],"often":[11],"encounter":[12],"the":[13,19,30,73,107,147,156,181,185],"corrupted":[14,22,53,84,98],"view":[15],"problem":[16],"in":[17,100],"which":[18],"data":[20,57,139],"are":[21,195],"by":[23],"two":[24],"different":[25,47,70,114,151],"types":[26],"of":[27,59],"noises,":[28,160],"i.e.,":[29],"intra-":[31,157],"inter-view":[33,159],"noises.":[34],"The":[35],"noises":[36],"may":[37],"affect":[38],"these":[39],"applications":[40,63],"that":[41,64,145,191],"commonly":[42],"acquire":[43],"complementary":[44,148,182],"representations":[45,68,77],"from":[46,55,69,150],"views.":[48,71,85,152],"Therefore,":[49],"how":[50],"to":[51,95,140,154,179],"denoise":[52,97],"views":[54,99],"is":[58,132],"great":[60],"importance":[61],"for":[62],"integrate":[65],"analyze":[67],"However,":[72],"heterogeneity":[74],"among":[75,113,184],"brings":[78],"a":[79,92,116,141,163],"significant":[80],"challenge":[81],"on":[82],"denoising":[83],"To":[86],"address":[87],"this":[88,101],"challenge,":[89],"propose":[91],"general":[93],"framework":[94],"jointly":[96],"paper.":[102],"Specifically,":[103],"aiming":[104],"at":[105],"capturing":[106],"semantic":[108],"complementarity":[109],"distributional":[111],"similarity":[112],"views,":[115],"novel":[117],"Heterogeneous":[118],"Linear":[119],"Metric":[120],"Learning":[121],"(HLML)":[122],"model":[123],"with":[124,171],"low-rank":[125],"regularization,":[126],"leave-one-out":[127],"validation,":[128],"pseudo-metric":[130],"constraints":[131,174],"proposed.":[133],"Our":[134],"method":[135,170],"linearly":[136],"maps":[137],"high-dimensional":[142],"feature-homogeneous":[143],"space":[144],"embeds":[146],"Furthermore,":[153],"remove":[155],"present":[162],"new":[164],"Multi-view":[165],"Semi-supervised":[166],"Collaborative":[167],"Denoising":[168],"(MSCD)":[169],"elementary":[172],"transformation":[173],"gradient":[176],"energy":[177],"competition":[178],"establish":[180],"relationship":[183],"heterogeneous":[186],"representations.":[187],"Experimental":[188],"results":[189],"demonstrate":[190],"our":[192],"proposed":[193],"methods":[194],"effective":[196],"efficient.":[198]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}