{"id":"https://openalex.org/W2913586401","doi":null,"title":"Convex coding","display_name":"Convex coding","publication_year":2009,"publication_date":"2009-06-18","ids":{"openalex":"https://openalex.org/W2913586401","mag":"2913586401"},"language":"en","primary_location":{"id":"pmh:oai:CiteSeerX.psu:10.1.1.298.516","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.298.516","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cs.mcgill.ca/~uai2009/papers/UAI2009_0128_f0b4d427233beb7420dfb226bc7c0958.pdf","raw_type":"text"},"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":null,"display_name":"David M. Bradley","orcid":"https://orcid.org/0000-0003-2952-2366","observed_orcids":["https://orcid.org/0000-0003-2952-2366"]},"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":"David M. Bradley","raw_affiliation_strings":["Carnegie Mellon University, Pittsburgh, PA"],"raw_orcid":"https://orcid.org/0000-0003-2952-2366","affiliations":[{"raw_affiliation_string":"Carnegie Mellon University, Pittsburgh, PA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5112411386","display_name":"James Andrew Bagnell","orcid":null,"observed_orcids":[]},"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":"J. Andrew Bagnell","raw_affiliation_strings":["Carnegie Mellon University, Pittsburgh, PA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University, Pittsburgh, PA","institution_ids":["https://openalex.org/I74973139"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I74973139"],"apc_list":null,"apc_paid":null,"fwci":2.3209,"has_fulltext":false,"cited_by_count":21,"citation_normalized_percentile":{"value":0.89224704,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"83","last_page":"90"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.8144999742507935,"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":0.8144999742507935,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.1615999937057495,"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/T10901","display_name":"Advanced Data Compression Techniques","score":0.002400000113993883,"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-coding","display_name":"sparse coding","score":0.9340000152587891},{"id":"https://openalex.org/keywords/convex-relaxation","display_name":"convex relaxation","score":0.9829999804496765},{"id":"https://openalex.org/keywords/boosting","display_name":"boosting","score":0.48100000619888306},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"sparse approximation","score":0.6729999780654907},{"id":"https://openalex.org/keywords/local-minima","display_name":"local minima","score":0.6209999918937683},{"id":"https://openalex.org/keywords/image-denoising","display_name":"image denoising","score":0.9039999842643738}],"concepts":[{"id":"https://openalex.org/C77637269","wikidata":"https://www.wikidata.org/wiki/Q7002051","display_name":"Neural coding","level":2,"score":0.6272544860839844},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5158792734146118},{"id":"https://openalex.org/C112680207","wikidata":"https://www.wikidata.org/wiki/Q714886","display_name":"Regular polygon","level":2,"score":0.49027684330940247},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.4721111059188843},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4567069709300995},{"id":"https://openalex.org/C157972887","wikidata":"https://www.wikidata.org/wiki/Q463359","display_name":"Convex optimization","level":3,"score":0.45486730337142944},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.44285839796066284},{"id":"https://openalex.org/C186633575","wikidata":"https://www.wikidata.org/wiki/Q845060","display_name":"Maxima and minima","level":2,"score":0.4355732500553131},{"id":"https://openalex.org/C154771677","wikidata":"https://www.wikidata.org/wiki/Q17098361","display_name":"K-SVD","level":3,"score":0.4158071279525757},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.37722495198249817},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.36014705896377563},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3538326025009155},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3032605051994324},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:CiteSeerX.psu:10.1.1.298.516","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.298.516","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cs.mcgill.ca/~uai2009/papers/UAI2009_0128_f0b4d427233beb7420dfb226bc7c0958.pdf","raw_type":"text"},{"id":"mag:2913586401","doi":null,"is_oa":false,"landing_page_url":"http://dl.acm.org/citation.cfm?id=1795125","pdf_url":null,"source":{"id":"https://openalex.org/S4306421103","display_name":"Uncertainty in Artificial Intelligence","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"Uncertainty in Artificial Intelligence","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":23,"referenced_works":["https://openalex.org/W48643329","https://openalex.org/W1570963478","https://openalex.org/W1678356000","https://openalex.org/W1974774078","https://openalex.org/W2056758595","https://openalex.org/W2074054045","https://openalex.org/W2097620723","https://openalex.org/W2105180921","https://openalex.org/W2105464873","https://openalex.org/W2108263314","https://openalex.org/W2113606819","https://openalex.org/W2122922389","https://openalex.org/W2129812935","https://openalex.org/W2132070206","https://openalex.org/W2132283655","https://openalex.org/W2148825261","https://openalex.org/W2164647001","https://openalex.org/W2167967601","https://openalex.org/W2168036472","https://openalex.org/W2170402521","https://openalex.org/W2296319761","https://openalex.org/W2571268788","https://openalex.org/W4302155765"],"related_works":["https://openalex.org/W2968938257","https://openalex.org/W7096090997","https://openalex.org/W2546653957","https://openalex.org/W2117259536","https://openalex.org/W3198226765","https://openalex.org/W3000380704","https://openalex.org/W2546067728","https://openalex.org/W7099504162","https://openalex.org/W136128527","https://openalex.org/W2415447328"],"abstract_inverted_index":{"Inspired":[0],"by":[1,58],"recent":[2],"work":[3],"on":[4,140],"convex":[5,93,113],"formulations":[6],"of":[7,22,41,53,61,95,135],"clustering":[8],"(Lashkari":[9],"&":[10,14,28,107],"Golland,":[11],"2008;":[12],"Nowozin":[13],"Bakir,":[15,108],"2008)":[16,109],"we":[17,34,90,131],"investigate":[18],"a":[19,39,54,59,67,92,102,112,118],"new":[20],"formulation":[21],"the":[23,96,124,133],"Sparse":[24],"Coding":[25],"Problem":[26],"(Olshausen":[27],"Field,":[29],"1997).":[30],"In":[31],"sparse":[32,45,80,97],"coding":[33,81,98,138],"attempt":[35],"to":[36,85,122,128],"simultaneously":[37],"represent":[38],"sequence":[40],"data-vectors":[42],"sparsely":[43],"(i.e.":[44],"approximation":[46],"(Tropp":[47],"et":[48],"al.,":[49],"2006))":[50],"in":[51],"terms":[52],"\u201ccode":[55],"\u201d":[56],"defined":[57],"set":[60],"basis":[62],"elements,":[63],"while":[64],"also":[65],"finding":[66],"code":[68,126],"that":[69,105],"enables":[70],"such":[71],"an":[72,141],"approximation.":[73],"As":[74],"existing":[75],"alternating":[76],"optimization":[77],"procedures":[78],"for":[79],"are":[82],"theoretically":[83],"prone":[84],"severe":[86],"local":[87],"minima":[88],"problems,":[89],"propose":[91],"relaxation":[94],"problem":[99],"and":[100],"derive":[101],"boosting-style":[103],"algorithm,":[104],"(Nowozin":[106],"serves":[110],"as":[111],"\u201cmaster":[114],"problem\u201d":[115],"which":[116],"calls":[117],"(potentially":[119],"non-convex)":[120],"sub-problem":[121],"identify":[123],"next":[125],"element":[127],"add.":[129],"Finally,":[130],"demonstrate":[132],"properties":[134],"our":[136],"boosted":[137],"algorithm":[139],"image":[142],"denoising":[143],"task.":[144],"1":[145]},"counts_by_year":[{"year":2020,"cited_by_count":2},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":3},{"year":2013,"cited_by_count":3},{"year":2012,"cited_by_count":3}],"updated_date":"2026-11-10T11:39:43.021295","created_date":"2019-02-21T00:00:00"}
