{"id":"https://openalex.org/W1579035185","doi":"https://doi.org/10.5075/epfl-thesis-4349","title":"Sparsity & [and] dictionaries - algorithms & [and] design","display_name":"Sparsity & [and] dictionaries - algorithms & [and] design","publication_year":2009,"publication_date":"2009-01-01","ids":{"openalex":"https://openalex.org/W1579035185","doi":"https://doi.org/10.5075/epfl-thesis-4349","mag":"1579035185"},"language":"en","primary_location":{"id":"pmh:oai:infoscience.tind.io:133433","is_oa":true,"landing_page_url":"http://infoscience.epfl.ch/record/133433","pdf_url":"https://infoscience.epfl.ch/record/133433/files/EPFL_TH4349.pdf","source":{"id":"https://openalex.org/S4306400487","display_name":"Infoscience (Ecole Polytechnique F\u00e9d\u00e9rale de Lausanne)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"doctoral thesis"},"type":"article","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://infoscience.epfl.ch/record/133433/files/EPFL_TH4349.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5011615599","display_name":"Karin Schnass","orcid":"https://orcid.org/0000-0002-4873-5570"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Schnass, Karin","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5011615599"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9997000098228455,"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"}},"topics":[{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9997000098228455,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9645000100135803,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9453999996185303,"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/sparse-approximation","display_name":"Sparse approximation","score":0.7515831589698792},{"id":"https://openalex.org/keywords/matching-pursuit","display_name":"Matching pursuit","score":0.6527303457260132},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6222970485687256},{"id":"https://openalex.org/keywords/basis","display_name":"Basis (linear algebra)","score":0.6130368113517761},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5431103706359863},{"id":"https://openalex.org/keywords/k-svd","display_name":"K-SVD","score":0.5362621545791626},{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.5247052907943726},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.5231931209564209},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5044270753860474},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.49030402302742004},{"id":"https://openalex.org/keywords/greedy-algorithm","display_name":"Greedy algorithm","score":0.4644724428653717},{"id":"https://openalex.org/keywords/basis-pursuit","display_name":"Basis pursuit","score":0.45397284626960754},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.43024179339408875},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.42636966705322266},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39913973212242126},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3659079670906067},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2740532159805298}],"concepts":[{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.7515831589698792},{"id":"https://openalex.org/C156872377","wikidata":"https://www.wikidata.org/wiki/Q6786281","display_name":"Matching pursuit","level":3,"score":0.6527303457260132},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6222970485687256},{"id":"https://openalex.org/C12426560","wikidata":"https://www.wikidata.org/wiki/Q189569","display_name":"Basis (linear algebra)","level":2,"score":0.6130368113517761},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5431103706359863},{"id":"https://openalex.org/C154771677","wikidata":"https://www.wikidata.org/wiki/Q17098361","display_name":"K-SVD","level":3,"score":0.5362621545791626},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.5247052907943726},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.5231931209564209},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5044270753860474},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.49030402302742004},{"id":"https://openalex.org/C51823790","wikidata":"https://www.wikidata.org/wiki/Q504353","display_name":"Greedy algorithm","level":2,"score":0.4644724428653717},{"id":"https://openalex.org/C99217422","wikidata":"https://www.wikidata.org/wiki/Q4867576","display_name":"Basis pursuit","level":4,"score":0.45397284626960754},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.43024179339408875},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.42636966705322266},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39913973212242126},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3659079670906067},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2740532159805298},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"pmh:oai:infoscience.tind.io:133433","is_oa":true,"landing_page_url":"http://infoscience.epfl.ch/record/133433","pdf_url":"https://infoscience.epfl.ch/record/133433/files/EPFL_TH4349.pdf","source":{"id":"https://openalex.org/S4306400487","display_name":"Infoscience (Ecole Polytechnique F\u00e9d\u00e9rale de Lausanne)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"doctoral thesis"},{"id":"doi:10.5075/epfl-thesis-4349","is_oa":true,"landing_page_url":"https://doi.org/10.5075/epfl-thesis-4349","pdf_url":null,"source":{"id":"https://openalex.org/S4306400488","display_name":"Infoscience (Ecole Polytechnique F\u00e9d\u00e9rale de Lausanne)","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":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"thesis"},{"id":"mag:1579035185","is_oa":false,"landing_page_url":"https://infoscience.epfl.ch/record/133433","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":null}],"best_oa_location":{"id":"pmh:oai:infoscience.tind.io:133433","is_oa":true,"landing_page_url":"http://infoscience.epfl.ch/record/133433","pdf_url":"https://infoscience.epfl.ch/record/133433/files/EPFL_TH4349.pdf","source":{"id":"https://openalex.org/S4306400487","display_name":"Infoscience (Ecole Polytechnique F\u00e9d\u00e9rale de Lausanne)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"doctoral thesis"},"sustainable_development_goals":[{"score":0.5799999833106995,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W1579035185.pdf","grobid_xml":"https://content.openalex.org/works/W1579035185.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2341210959","https://openalex.org/W2150359011","https://openalex.org/W2952153281","https://openalex.org/W2010161441","https://openalex.org/W2528294243","https://openalex.org/W2585831915","https://openalex.org/W1489635965","https://openalex.org/W2809895845","https://openalex.org/W1550714309","https://openalex.org/W1936178334","https://openalex.org/W2103955025","https://openalex.org/W2022615714","https://openalex.org/W2115736876","https://openalex.org/W2126603275","https://openalex.org/W73089934","https://openalex.org/W2464641472","https://openalex.org/W2529985366","https://openalex.org/W2111304728","https://openalex.org/W2346728112","https://openalex.org/W2610790008"],"abstract_inverted_index":{"With":[0],"the":[1,7,47,64,78,104,120,141,211,228,263,266,273,346,352,366,384],"flood":[2,35],"of":[3,50,57,67,106,122,140,146,158,188,206,230,265,272,275,313,316,330,339,374,386,389],"information":[4],"available":[5],"today":[6],"question":[8,354],"how":[9,308,355],"to":[10,19,21,25,32,37,63,119,199,233,248,257,279,301,309,324,345,356,368],"deal":[11],"with":[12,23,131,144,171,412],"high":[13,413],"dimensional":[14],"data/signals,":[15],"which":[16],"are":[17,90,236,410],"cumbersome":[18],"handle,":[20],"calculate":[22],"and":[24,125,134,150,181,214,333,350,379,395],"store,":[26],"is":[27,36,46,161,224,254],"highly":[28],"important.":[29],"One":[30],"approach":[31],"reducing":[33],"this":[34,68],"find":[38,357],"sparse":[39,79,91,108,129,237,251,290,347,361],"signal":[40,44,88,252,267],"representations,":[41,109,130],"as":[42,259,262],"a":[43,51,55,75,93,100,154,172,240,244,250,270,314,326,358,370,375,387,393,396,400],"that":[45,163,175,182,222,235,285,293,383],"linear":[48],"combination":[49],"few":[52,65],"elements":[53,277],"from":[54,153],"pool":[56],"building":[58,72,97],"blocks,":[59,98],"can":[60,168,297],"be":[61,169,299],"reduced":[62],"coefficients":[66],"representation.":[69],"If":[70],"these":[71,331,408],"blocks":[73],"form":[74],"basis,":[76],"finding":[77,112,128],"representation":[80,348],"poses":[81],"no":[82],"problem":[83,349],"but":[84,110,242,268,292],"unfortunately":[85],"not":[86,177,238,255],"many":[87,260],"classes":[89],"in":[92,197,239,243],"basis.":[94],"Taking":[95],"more":[96,155,200,220],"i.e.":[99],"redundant":[101,245],"dictionary,":[102],"increases":[103],"chances":[105],"having":[107],"actually":[111],"them":[113],"becomes":[114],"very":[115],"hard.":[116],"This":[117],"led":[118],"development":[121],"numerous":[123],"strategies":[124],"algorithms":[126,167],"for":[127,337],"varying":[132],"complexity":[133],"success":[135],"rate.":[136],"The":[137,203],"first":[138],"part":[139,205],"thesis":[142,207],"deals":[143],"two":[145],"those":[147,165],"algorithms,":[148],"Thresholding":[149],"Matching":[151],"Pursuit,":[152],"theoretical":[156],"point":[157],"view.":[159],"It":[160],"shown":[162],"both":[164],"greedy":[166],"improved":[170],"little":[173],"trick,":[174],"does":[176],"increase":[178],"their":[179,185,189,294],"complexity,":[180],"when":[183,407],"considering":[184],"average":[186],"instead":[187],"worst":[190],"case":[191],"performance":[192],"they":[193],"perform":[194],"quite":[195],"well":[196],"comparison":[198],"complex":[201],"methods.":[202],"second":[204],"treats":[208],"questions":[209],"concerning":[210],"whole":[212],"dictionary":[213,276,327,359,371,394],"its":[215],"properties.":[216],"First":[217],"it":[218,253,336],"gives":[219],"evidence":[221],"sparsity":[223],"useful":[225],"by":[226,318],"extending":[227],"concept":[229],"compressed":[231],"sensing":[232],"signals":[234,317,391],"basis":[241],"dictionary.":[246],"Thus":[247],"record":[249],"necessary":[256],"make":[258],"measurements":[261],"dimension":[264],"only":[269,288],"multiple":[271],"number":[274],"used":[278],"represent":[280],"it.":[281],"Next":[282],"we":[283,306,342],"show":[284],"dictionaries":[286],"cannot":[287],"provide":[289,380],"representations":[291],"geometric":[295],"properties":[296],"also":[298,404],"exploited":[300],"model":[302,310],"data":[303],"structures.":[304],"Here":[305],"explain":[307],"different":[311],"subclasses":[312],"class":[315],"incoherent":[319],"subspaces,":[320],"present":[321],"an":[322],"algorithm":[323],"learn":[325,369],"made":[328],"out":[329],"subspaces":[332],"then":[334],"use":[335],"classification":[338],"faces.":[340],"Finally":[341],"turn":[343],"back":[344],"study":[351],"fundamental":[353],"providing":[360],"representations.":[362],"We":[363,403],"pick":[364],"up":[365],"idea":[367],"via":[372],"minimisation":[373],"continuous":[376],"cost":[377],"function":[378],"conditions,":[381],"guaranteeing":[382],"decomposition":[385],"collection":[388],"training":[390],"into":[392],"coefficient":[397],"matrix":[398],"constitutes":[399],"local":[401],"minimum.":[402],"analyse":[405],"statistically":[406],"conditions":[409],"fulfilled":[411],"probability.":[414]},"counts_by_year":[],"updated_date":"2025-11-06T06:51:31.235846","created_date":"2025-10-10T00:00:00"}