{"id":"https://openalex.org/W2162221686","doi":null,"title":"Efficient supervised sparse analysis and synthesis operators","display_name":"Efficient supervised sparse analysis and synthesis operators","publication_year":2013,"publication_date":"2013-01-01","ids":{"openalex":"https://openalex.org/W2162221686","mag":"2162221686"},"language":"en","primary_location":{"id":"mag:2162221686","doi":null,"is_oa":false,"landing_page_url":"https://papers.nips.cc/paper/2013/file/7380ad8a673226ae47fce7bff88e9c33-Paper.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4363606243","display_name":"neural information processing systems","issn_l":"1049-5258","issn":["1049-5258"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","norway-2"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"Neural Information Processing Systems","raw_type":null},"volume":null,"type":"article","is_traditional":true,"indexed_in":[],"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/A5088180679","display_name":"Pablo Sprechmann","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I170897317","display_name":"Duke University","ror":"https://ror.org/00py81415","country_code":"US","type":"education","lineage":["https://openalex.org/I170897317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Pablo Sprechmann","raw_affiliation_strings":["Duke University, Durham, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Duke University, Durham, United States","institution_ids":["https://openalex.org/I170897317"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075459505","display_name":"Roee Litman","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I16391192","display_name":"Tel Aviv University","ror":"https://ror.org/04mhzgx49","country_code":"IL","type":"education","lineage":["https://openalex.org/I16391192"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Roee Litman","raw_affiliation_strings":["Tel Aviv University, Tel Aviv, Israel"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tel Aviv University, Tel Aviv, Israel","institution_ids":["https://openalex.org/I16391192"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074194961","display_name":"Tal Ben Yakar","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tal Ben Yakar","raw_affiliation_strings":["Massachusetts Institute of Technology, Cambridge, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Massachusetts Institute of Technology, Cambridge, United States","institution_ids":["https://openalex.org/I63966007"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109277461","display_name":"Alexander M. Bronstein","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I16391192","display_name":"Tel Aviv University","ror":"https://ror.org/04mhzgx49","country_code":"IL","type":"education","lineage":["https://openalex.org/I16391192"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Alexander M. Bronstein","raw_affiliation_strings":["Tel Aviv University, Tel Aviv, Israel"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tel Aviv University, Tel Aviv, Israel","institution_ids":["https://openalex.org/I16391192"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025218580","display_name":"Guillermo Sapiro","orcid":"https://orcid.org/0000-0001-9190-6964","observed_orcids":["https://orcid.org/0000-0001-9190-6964"]},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Guillermo Sapiro","raw_affiliation_strings":["University of Minnesota, Minneapolis, United States"],"raw_orcid":"https://orcid.org/0000-0001-9190-6964","affiliations":[{"raw_affiliation_string":"University of Minnesota, Minneapolis, United States","institution_ids":["https://openalex.org/I130238516"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":5.0818,"has_fulltext":false,"cited_by_count":53,"citation_normalized_percentile":{"value":0.95410027,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"26","issue":null,"first_page":"908","last_page":"916"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9854000210762024,"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"}},"topics":[{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9854000210762024,"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/T11210","display_name":"Mathematical Analysis and Transform Methods","score":0.006500000134110451,"subfield":{"id":"https://openalex.org/subfields/2604","display_name":"Applied Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.0020000000949949026,"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/bi-level-optimization","display_name":"bi-level optimization","score":0.8830000162124634},{"id":"https://openalex.org/keywords/sparse-priors","display_name":"sparse priors","score":0.6069999933242798},{"id":"https://openalex.org/keywords/sparse-codes","display_name":"sparse codes","score":0.49000000953674316},{"id":"https://openalex.org/keywords/convolutional-neural-networks","display_name":"convolutional neural networks","score":0.7279999852180481},{"id":"https://openalex.org/keywords/musical-analysis","display_name":"musical analysis","score":0.7639999985694885},{"id":"https://openalex.org/keywords/image-processing","display_name":"image processing","score":0.9779999852180481}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.718454122543335},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5515208840370178},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.5347781181335449},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5219725370407104},{"id":"https://openalex.org/C3309286","wikidata":"https://www.wikidata.org/wiki/Q4907693","display_name":"Bilevel optimization","level":3,"score":0.5117645263671875},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.48354268074035645},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4366976022720337},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.36946171522140503},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.3359220623970032},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3236679434776306},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.31757837533950806},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15781444311141968},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C37914503","wikidata":"https://www.wikidata.org/wiki/Q156495","display_name":"Mathematical physics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"mag:2162221686","doi":null,"is_oa":false,"landing_page_url":"https://papers.nips.cc/paper/2013/file/7380ad8a673226ae47fce7bff88e9c33-Paper.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4363606243","display_name":"neural information processing systems","issn_l":"1049-5258","issn":["1049-5258"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","norway-2"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"Neural Information Processing Systems","raw_type":null},{"id":"mag:2552905758","doi":null,"is_oa":false,"landing_page_url":"http://papers.nips.cc/paper/5002-supervised-sparse-analysis-and-synthesis-operators.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4363606243","display_name":"neural information processing systems","issn_l":"1049-5258","issn":["1049-5258"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","norway-2"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"Neural Information Processing Systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1759597718","https://openalex.org/W1977777127","https://openalex.org/W2076608692","https://openalex.org/W2100556411","https://openalex.org/W2103559027","https://openalex.org/W2109320267","https://openalex.org/W2110007838","https://openalex.org/W2114122776","https://openalex.org/W2115755118","https://openalex.org/W2116861100","https://openalex.org/W2118103795","https://openalex.org/W2124659975","https://openalex.org/W2135046866","https://openalex.org/W2142211803","https://openalex.org/W2144414181","https://openalex.org/W2145889472","https://openalex.org/W2146482778","https://openalex.org/W2152375848","https://openalex.org/W2153663612","https://openalex.org/W2160547390","https://openalex.org/W2161516371","https://openalex.org/W2163112044","https://openalex.org/W2257784670","https://openalex.org/W2326240252","https://openalex.org/W2798766386","https://openalex.org/W2963811803"],"related_works":["https://openalex.org/W2552905758","https://openalex.org/W7097394055","https://openalex.org/W2049893860","https://openalex.org/W2793847116","https://openalex.org/W2963811803","https://openalex.org/W7074649371","https://openalex.org/W2787026710","https://openalex.org/W2146738562","https://openalex.org/W4221144573","https://openalex.org/W2120047933"],"abstract_inverted_index":{"In":[0,131],"this":[1,135],"paper,":[2],"we":[3,106],"propose":[4,107],"a":[5,17,47,64,85,108,122,138],"new":[6],"and":[7,29,34,157],"computationally":[8],"efficient":[9],"framework":[10],"for":[11],"learning":[12,88],"sparse":[13,27,104],"models.":[14],"We":[15,146],"formulate":[16],"unified":[18],"approach":[19,80],"that":[20],"contains":[21],"as":[22,46,84],"particular":[23],"cases":[24],"models":[25,120,150],"promoting":[26],"synthesis":[28],"analysis":[30,156],"type":[31],"of":[32,40,87,110,116,124,128,141],"priors,":[33],"mixtures":[35],"thereof.":[36],"The":[37],"supervised":[38],"training":[39],"the":[41,53,59,73,118,125,132,148],"proposed":[42,149],"model":[43],"is":[44],"formulated":[45],"bilevel":[48],"optimization":[49],"problem,":[50],"in":[51,154],"which":[52],"operators":[54,74],"are":[55],"optimized":[56],"to":[57,75,101,137],"achieve":[58],"best":[60],"possible":[61],"performance":[62],"on":[63,96,151],"specific":[65],"task,":[66],"e.g.,":[67],"reconstruction":[68],"or":[69],"classification.":[70],"By":[71],"restricting":[72],"be":[76,82],"shift":[77],"invariant,":[78],"our":[79],"can":[81],"thought":[83],"way":[86,109,140],"analysis+synthesis":[89],"sparsity-promoting":[90],"convolutional":[91,144],"operators.":[92],"Leveraging":[93],"recent":[94],"ideas":[95],"fast":[97],"trainable":[98],"regressors":[99],"designed":[100],"approximate":[102],"exact":[103,129],"codes,":[105],"constructing":[111,142],"feed-forward":[112],"neural":[113],"networks":[114],"capable":[115],"approximating":[117],"learned":[119],"at":[121],"fraction":[123],"computational":[126],"cost":[127],"solvers.":[130],"shift-invariant":[133],"case,":[134],"leads":[136],"principled":[139],"task-specific":[143],"networks.":[145],"illustrate":[147],"several":[152],"experiments":[153],"music":[155],"image":[158],"processing":[159],"applications.":[160]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":8},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":6},{"year":2016,"cited_by_count":6},{"year":2015,"cited_by_count":5},{"year":2014,"cited_by_count":3}],"updated_date":"2026-11-08T12:12:28.789561","created_date":"2016-06-24T00:00:00"}