{"id":"https://openalex.org/W1569191925","doi":"https://doi.org/10.1109/icme.2015.7177438","title":"Joint kernel dictionary and classifier learning for sparse coding via locality preserving K-SVD","display_name":"Joint kernel dictionary and classifier learning for sparse coding via locality preserving K-SVD","publication_year":2015,"publication_date":"2015-06-01","ids":{"openalex":"https://openalex.org/W1569191925","doi":"https://doi.org/10.1109/icme.2015.7177438","mag":"1569191925"},"language":"en","primary_location":{"id":"doi:10.1109/icme.2015.7177438","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme.2015.7177438","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Conference on Multimedia and Expo (ICME)","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/A5101606029","display_name":"Weiyang Liu","orcid":"https://orcid.org/0000-0002-8234-3263"},"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"]},{"id":"https://openalex.org/I111483173","display_name":"King University","ror":"https://ror.org/01evb6z23","country_code":"US","type":"education","lineage":["https://openalex.org/I111483173"]}],"countries":["CN","US"],"is_corresponding":true,"raw_author_name":"Weiyang Liu","raw_affiliation_strings":["School of ECE Peking University","School of ECE, Peking University, China"],"affiliations":[{"raw_affiliation_string":"School of ECE Peking University","institution_ids":["https://openalex.org/I20231570","https://openalex.org/I111483173"]},{"raw_affiliation_string":"School of ECE, Peking University, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054586129","display_name":"Zhiding Yu","orcid":"https://orcid.org/0000-0003-1776-996X"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhiding Yu","raw_affiliation_strings":["Dept. of ECE, Carnegie Mellon University","Dept. of ECE, Carnegie Mellon University, United States"],"affiliations":[{"raw_affiliation_string":"Dept. of ECE, Carnegie Mellon University","institution_ids":["https://openalex.org/I74973139"]},{"raw_affiliation_string":"Dept. of ECE, Carnegie Mellon University, United States","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037873810","display_name":"Meng Yang","orcid":"https://orcid.org/0000-0002-0795-3221"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Meng Yang","raw_affiliation_strings":["College of Computer Science & Software Engineering, Shenzhen University","College of Computer Science and Software Engineering, Shenzhen University,China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science & Software Engineering, Shenzhen University","institution_ids":["https://openalex.org/I180726961"]},{"raw_affiliation_string":"College of Computer Science and Software Engineering, Shenzhen University,China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103856045","display_name":"Lijia Lu","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"]},{"id":"https://openalex.org/I111483173","display_name":"King University","ror":"https://ror.org/01evb6z23","country_code":"US","type":"education","lineage":["https://openalex.org/I111483173"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Lijia Lu","raw_affiliation_strings":["School of ECE Peking University","School of ECE, Peking University, China"],"affiliations":[{"raw_affiliation_string":"School of ECE Peking University","institution_ids":["https://openalex.org/I20231570","https://openalex.org/I111483173"]},{"raw_affiliation_string":"School of ECE, Peking University, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002795838","display_name":"Yuexian Zou","orcid":"https://orcid.org/0000-0001-9999-6140"},"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"]},{"id":"https://openalex.org/I111483173","display_name":"King University","ror":"https://ror.org/01evb6z23","country_code":"US","type":"education","lineage":["https://openalex.org/I111483173"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Yuexian Zou","raw_affiliation_strings":["School of ECE Peking University","School of ECE, Peking University, China"],"affiliations":[{"raw_affiliation_string":"School of ECE Peking University","institution_ids":["https://openalex.org/I20231570","https://openalex.org/I111483173"]},{"raw_affiliation_string":"School of ECE, Peking University, China","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5101606029"],"corresponding_institution_ids":["https://openalex.org/I111483173","https://openalex.org/I20231570"],"apc_list":null,"apc_paid":null,"fwci":1.6569,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":{"value":0.88837895,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"3 3","issue":null,"first_page":"1","last_page":"6"},"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9993000030517578,"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/T10688","display_name":"Image and Signal Denoising Methods","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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6658085584640503},{"id":"https://openalex.org/keywords/locality","display_name":"Locality","score":0.6388548612594604},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6085983514785767},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5911492109298706},{"id":"https://openalex.org/keywords/k-svd","display_name":"K-SVD","score":0.5635280609130859},{"id":"https://openalex.org/keywords/neural-coding","display_name":"Neural coding","score":0.5536553859710693},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5437629222869873},{"id":"https://openalex.org/keywords/dictionary-learning","display_name":"Dictionary learning","score":0.5244244337081909},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.4480455815792084},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.2849876284599304},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19498500227928162},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.06778746843338013}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6658085584640503},{"id":"https://openalex.org/C2779808786","wikidata":"https://www.wikidata.org/wiki/Q6664603","display_name":"Locality","level":2,"score":0.6388548612594604},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6085983514785767},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5911492109298706},{"id":"https://openalex.org/C154771677","wikidata":"https://www.wikidata.org/wiki/Q17098361","display_name":"K-SVD","level":3,"score":0.5635280609130859},{"id":"https://openalex.org/C77637269","wikidata":"https://www.wikidata.org/wiki/Q7002051","display_name":"Neural coding","level":2,"score":0.5536553859710693},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5437629222869873},{"id":"https://openalex.org/C2988886741","wikidata":"https://www.wikidata.org/wiki/Q25304494","display_name":"Dictionary learning","level":3,"score":0.5244244337081909},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.4480455815792084},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.2849876284599304},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19498500227928162},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.06778746843338013},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icme.2015.7177438","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme.2015.7177438","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Conference on Multimedia and Expo (ICME)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7300000190734863,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W1560724230","https://openalex.org/W1587559447","https://openalex.org/W1808256548","https://openalex.org/W1963932623","https://openalex.org/W1979920826","https://openalex.org/W1982405594","https://openalex.org/W2017214807","https://openalex.org/W2027805700","https://openalex.org/W2027922120","https://openalex.org/W2037122648","https://openalex.org/W2046769852","https://openalex.org/W2088843485","https://openalex.org/W2123921160","https://openalex.org/W2129812935","https://openalex.org/W2130951397","https://openalex.org/W2134563198","https://openalex.org/W2140245639","https://openalex.org/W2142848040","https://openalex.org/W2146047955","https://openalex.org/W2149861038","https://openalex.org/W2153663612","https://openalex.org/W2157639439","https://openalex.org/W2160547390","https://openalex.org/W2162915993","https://openalex.org/W2166049352","https://openalex.org/W2536599074","https://openalex.org/W3195149063","https://openalex.org/W4313169793","https://openalex.org/W6640897813","https://openalex.org/W6645387675","https://openalex.org/W6672484794","https://openalex.org/W6679809621","https://openalex.org/W6680798698","https://openalex.org/W6681521150","https://openalex.org/W6683265229","https://openalex.org/W7074671674"],"related_works":["https://openalex.org/W2161305109","https://openalex.org/W2008821896","https://openalex.org/W2244609343","https://openalex.org/W2364118486","https://openalex.org/W2793063187","https://openalex.org/W3012953444","https://openalex.org/W204290405","https://openalex.org/W2026350744","https://openalex.org/W2084716923","https://openalex.org/W2583520174"],"abstract_inverted_index":{"We":[0],"present":[1],"a":[2,25,62],"locality":[3,26,42,49],"preserving":[4,27],"K-SVD":[5],"(LP-KSVD)":[6],"algorithm":[7],"for":[8],"joint":[9],"dictionary":[10,37],"and":[11,14,36,39,65,96],"classifier":[12],"learning,":[13],"further":[15],"incorporate":[16],"kernel":[17,76],"into":[18],"our":[19],"framework.":[20],"In":[21],"LP-KSVD,":[22],"we":[23,68],"construct":[24],"term":[28],"based":[29],"on":[30,104],"the":[31,41,48,54,70,75,89],"relations":[32],"between":[33],"input":[34],"samples":[35,79],"atoms,":[38],"introduce":[40],"via":[43],"nearest":[44],"neighborhood":[45],"to":[46,74],"enforce":[47],"of":[50,80],"representation.":[51],"Motivated":[52],"by":[53],"fact":[55],"that":[56],"locality-related":[57],"methods":[58],"works":[59],"better":[60],"in":[61],"more":[63,84],"discriminative":[64],"separable":[66],"space,":[67,77],"map":[69],"original":[71],"feature":[72],"space":[73],"where":[78],"different":[81],"classes":[82],"become":[83],"separable.":[85],"Experimental":[86],"results":[87],"show":[88],"proposed":[90],"approach":[91],"has":[92],"strong":[93],"discrimination":[94],"power":[95],"is":[97],"comparable":[98],"or":[99],"outperforms":[100],"some":[101],"state-of-the-art":[102],"approaches":[103],"public":[105],"databases.":[106]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}