{"id":"https://openalex.org/W2490303931","doi":"https://doi.org/10.1142/s0218001416600077","title":"Structure Feature Learning Method for Incomplete Data","display_name":"Structure Feature Learning Method for Incomplete Data","publication_year":2016,"publication_date":"2016-07-25","ids":{"openalex":"https://openalex.org/W2490303931","doi":"https://doi.org/10.1142/s0218001416600077","mag":"2490303931"},"language":"en","primary_location":{"id":"doi:10.1142/s0218001416600077","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218001416600077","pdf_url":null,"source":{"id":"https://openalex.org/S41486457","display_name":"International Journal of Pattern Recognition and Artificial Intelligence","issn_l":"0218-0014","issn":["0218-0014","1793-6381"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Pattern Recognition and Artificial Intelligence","raw_type":"journal-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/A5046345742","display_name":"Xiabing Zhou","orcid":"https://orcid.org/0000-0002-6497-8118"},"institutions":[{"id":"https://openalex.org/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiabing Zhou","raw_affiliation_strings":["Institute of Automation, Chinese Academy of Sciences, P. R. China","Key Laboratory of Machine Perception, Ministry of Education, Peking University, Beijing, 100871, P. R. China"],"affiliations":[{"raw_affiliation_string":"Institute of Automation, Chinese Academy of Sciences, P. R. China","institution_ids":["https://openalex.org/I4210094879","https://openalex.org/I19820366"]},{"raw_affiliation_string":"Key Laboratory of Machine Perception, Ministry of Education, Peking University, Beijing, 100871, P. R. China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050027791","display_name":"Xingxing Xing","orcid":null},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xingxing Xing","raw_affiliation_strings":["Key Laboratory of Machine Perception, Ministry of Education, Peking University, Beijing, 100871, P. R. China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Machine Perception, Ministry of Education, Peking University, Beijing, 100871, P. R. China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103010973","display_name":"Lei Han","orcid":"https://orcid.org/0000-0003-1743-8124"},"institutions":[{"id":"https://openalex.org/I102322142","display_name":"Rutgers, The State University of New Jersey","ror":"https://ror.org/05vt9qd57","country_code":"US","type":"education","lineage":["https://openalex.org/I102322142"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lei Han","raw_affiliation_strings":["486 Hill Center, Piscataway, NJ, 08854, Rutgers University, USA"],"affiliations":[{"raw_affiliation_string":"486 Hill Center, Piscataway, NJ, 08854, Rutgers University, USA","institution_ids":["https://openalex.org/I102322142"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046608695","display_name":"Haikun Hong","orcid":null},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haikun Hong","raw_affiliation_strings":["Key Laboratory of Machine Perception, Ministry of Education, Peking University, Beijing, 100871, P. R. China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Machine Perception, Ministry of Education, Peking University, Beijing, 100871, P. R. China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064314482","display_name":"Kaigui Bian","orcid":null},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kaigui Bian","raw_affiliation_strings":["Key Laboratory of Machine Perception, Ministry of Education, Peking University, Beijing, 100871, P. R. China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Machine Perception, Ministry of Education, Peking University, Beijing, 100871, P. R. China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100825074","display_name":"Kunqing Xie","orcid":null},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kunqing Xie","raw_affiliation_strings":["Key Laboratory of Machine Perception, Ministry of Education, Peking University, Beijing, 100871, P. R. China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Machine Perception, Ministry of Education, Peking University, Beijing, 100871, P. R. China","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5046345742"],"corresponding_institution_ids":["https://openalex.org/I19820366","https://openalex.org/I20231570","https://openalex.org/I4210094879"],"apc_list":null,"apc_paid":null,"fwci":1.2854,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.86792231,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"30","issue":"09","first_page":"1660007","last_page":"1660007"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9919000267982483,"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"}},"topics":[{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9919000267982483,"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"}},{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9839000105857849,"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"}},{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":0.9702000021934509,"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/computer-science","display_name":"Computer science","score":0.7348177433013916},{"id":"https://openalex.org/keywords/imputation","display_name":"Imputation (statistics)","score":0.6972494721412659},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.6621266603469849},{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.6521762609481812},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.529630720615387},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5000066757202148},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4752209782600403},{"id":"https://openalex.org/keywords/smoothness","display_name":"Smoothness","score":0.4600197672843933},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.45725008845329285},{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.45613154768943787},{"id":"https://openalex.org/keywords/synthetic-data","display_name":"Synthetic data","score":0.4166545569896698},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32503747940063477},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12490978837013245}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7348177433013916},{"id":"https://openalex.org/C58041806","wikidata":"https://www.wikidata.org/wiki/Q1660484","display_name":"Imputation (statistics)","level":3,"score":0.6972494721412659},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.6621266603469849},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.6521762609481812},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.529630720615387},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5000066757202148},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4752209782600403},{"id":"https://openalex.org/C102634674","wikidata":"https://www.wikidata.org/wiki/Q868473","display_name":"Smoothness","level":2,"score":0.4600197672843933},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45725008845329285},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.45613154768943787},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.4166545569896698},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32503747940063477},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12490978837013245},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1142/s0218001416600077","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218001416600077","pdf_url":null,"source":{"id":"https://openalex.org/S41486457","display_name":"International Journal of Pattern Recognition and Artificial Intelligence","issn_l":"0218-0014","issn":["0218-0014","1793-6381"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Pattern Recognition and Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.6000000238418579}],"awards":[{"id":"https://openalex.org/G7984653286","display_name":null,"funder_award_id":"61473006","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":42,"referenced_works":["https://openalex.org/W263545290","https://openalex.org/W1551136530","https://openalex.org/W1789901068","https://openalex.org/W1859831128","https://openalex.org/W1986661373","https://openalex.org/W1989060270","https://openalex.org/W1995515386","https://openalex.org/W2011359124","https://openalex.org/W2020641160","https://openalex.org/W2024182233","https://openalex.org/W2032365301","https://openalex.org/W2032685209","https://openalex.org/W2044758663","https://openalex.org/W2049633694","https://openalex.org/W2060240123","https://openalex.org/W2092403294","https://openalex.org/W2096532744","https://openalex.org/W2103972604","https://openalex.org/W2117853077","https://openalex.org/W2120872934","https://openalex.org/W2122904721","https://openalex.org/W2122966827","https://openalex.org/W2127532853","https://openalex.org/W2134332047","https://openalex.org/W2135046866","https://openalex.org/W2138019504","https://openalex.org/W2145446394","https://openalex.org/W2145962650","https://openalex.org/W2146130798","https://openalex.org/W2151544854","https://openalex.org/W2157957962","https://openalex.org/W2159400887","https://openalex.org/W2163150789","https://openalex.org/W2166597282","https://openalex.org/W2167732364","https://openalex.org/W2172250608","https://openalex.org/W2174160981","https://openalex.org/W2183875436","https://openalex.org/W2246109554","https://openalex.org/W2480680997","https://openalex.org/W2611328865","https://openalex.org/W3101782091"],"related_works":["https://openalex.org/W4283217487","https://openalex.org/W3215437053","https://openalex.org/W2804897963","https://openalex.org/W2365820551","https://openalex.org/W1588995113","https://openalex.org/W3027068985","https://openalex.org/W2246127447","https://openalex.org/W1641882428","https://openalex.org/W4205352500","https://openalex.org/W3023546548"],"abstract_inverted_index":{"Learning":[0],"with":[1,26,103],"incomplete":[2,27,104],"data":[3,13,83,105,125,144],"remains":[4],"challenging":[5],"in":[6,52,71,81],"many":[7],"real-world":[8,184],"applications":[9],"especially":[10],"when":[11],"the":[12,35,40,48,53,62,66,82,124,129,134,140,143,158,164,195],"is":[14,152],"high-dimensional":[15],"and":[16,65,77,95,116,133,161,183],"dynamic.":[17],"Many":[18],"imputation-based":[19],"algorithms":[20,31],"have":[21],"been":[22],"proposed":[23,149],"to":[24,38,90,122,138,157,170],"handle":[25],"data,":[28,54],"where":[29,142],"these":[30,44,92],"use":[32,47],"statistics":[33],"of":[34],"historical":[36],"information":[37,50,76,94],"remedy":[39],"missing":[41,67],"parts.":[42],"However,":[43],"methods":[45],"merely":[46],"structural":[49,93,97],"existing":[51],"which":[55],"are":[56,146],"very":[57],"helpful":[58],"for":[59,101,172],"sharing":[60,126],"between":[61],"complete":[63],"entries":[64,145],"ones.":[68],"For":[69],"example,":[70],"traffic":[72,186],"system,":[73],"some":[74],"group":[75,118,136],"temporal":[78,130],"smoothness":[79,131],"exist":[80],"structure.":[84],"In":[85],"this":[86],"paper,":[87],"we":[88,162],"propose":[89],"incorporate":[91],"develop":[96],"feature":[98,135],"leaning":[99],"method":[100,169,193],"learning":[102],"(SFLIC).":[106],"The":[107,148],"SFLIC":[108,150],"model":[109,151,159,179],"adopt":[110,163],"a":[111,117,153],"fused":[112],"Lasso":[113,119],"based":[114],"regularizer":[115,121],"style":[120],"enlarge":[123],"along":[127],"both":[128,181],"level":[132,137],"fill":[139],"gap":[141],"missing.":[147],"nonsmooth":[154],"function":[155],"according":[156],"parameters,":[160],"smoothing":[165],"proximal":[166],"gradient":[167],"(SPG)":[168],"seek":[171],"an":[173],"efficient":[174],"solution.":[175],"We":[176],"evaluate":[177],"our":[178,192],"on":[180],"synthetic":[182],"highway":[185],"datasets.":[187],"Experimental":[188],"results":[189],"show":[190],"that":[191],"outperforms":[194],"state-of-the-art":[196],"methods.":[197]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}