{"id":"https://openalex.org/W2153705932","doi":"https://doi.org/10.1109/cdc.2007.4434778","title":"Greedy algorithms for dirac mixture approximation of arbitrary probability density functions","display_name":"Greedy algorithms for dirac mixture approximation of arbitrary probability density functions","publication_year":2007,"publication_date":"2007-01-01","ids":{"openalex":"https://openalex.org/W2153705932","doi":"https://doi.org/10.1109/cdc.2007.4434778","mag":"2153705932"},"language":"en","primary_location":{"id":"doi:10.1109/cdc.2007.4434778","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cdc.2007.4434778","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2007 46th IEEE Conference on Decision and Control","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.5445/ir/1000034824","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5055331421","display_name":"Uwe D. Hanebeck","orcid":"https://orcid.org/0000-0001-9870-2331"},"institutions":[{"id":"https://openalex.org/I102335020","display_name":"Karlsruhe Institute of Technology","ror":"https://ror.org/04t3en479","country_code":"DE","type":"education","lineage":["https://openalex.org/I102335020","https://openalex.org/I1305996414"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Uwe D. Hanebeck","raw_affiliation_strings":["Institute of Computer Science and Engineering, Universit\u00e4t Karlsruhe, Germany"],"affiliations":[{"raw_affiliation_string":"Institute of Computer Science and Engineering, Universit\u00e4t Karlsruhe, Germany","institution_ids":["https://openalex.org/I102335020"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5075440347","display_name":"Oliver C. Schrempf","orcid":null},"institutions":[{"id":"https://openalex.org/I102335020","display_name":"Karlsruhe Institute of Technology","ror":"https://ror.org/04t3en479","country_code":"DE","type":"education","lineage":["https://openalex.org/I102335020","https://openalex.org/I1305996414"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Oliver C. Schrempf","raw_affiliation_strings":["Institute of Computer Science and Engineering, Universit\u00e4t Karlsruhe, Germany"],"affiliations":[{"raw_affiliation_string":"Institute of Computer Science and Engineering, Universit\u00e4t Karlsruhe, Germany","institution_ids":["https://openalex.org/I102335020"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5055331421"],"corresponding_institution_ids":["https://openalex.org/I102335020"],"apc_list":null,"apc_paid":null,"fwci":3.8637,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.9377273,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"5099","issue":null,"first_page":"3065","last_page":"3071"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9983000159263611,"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/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9983000159263611,"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/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9980999827384949,"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9957000017166138,"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/measure","display_name":"Measure (data warehouse)","score":0.7418731451034546},{"id":"https://openalex.org/keywords/probability-density-function","display_name":"Probability density function","score":0.6610233783721924},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.619531512260437},{"id":"https://openalex.org/keywords/greedy-algorithm","display_name":"Greedy algorithm","score":0.5105611085891724},{"id":"https://openalex.org/keywords/a-priori-and-a-posteriori","display_name":"A priori and a posteriori","score":0.4881911873817444},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.47494176030158997},{"id":"https://openalex.org/keywords/dirac","display_name":"Dirac (video compression format)","score":0.4676280617713928},{"id":"https://openalex.org/keywords/quadratic-equation","display_name":"Quadratic equation","score":0.45900461077690125},{"id":"https://openalex.org/keywords/approximation-algorithm","display_name":"Approximation algorithm","score":0.453539103269577},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.42356839776039124},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.40497756004333496},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.3996945023536682},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.39909809827804565},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.22940102219581604},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.103658527135849},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.082816481590271},{"id":"https://openalex.org/keywords/quantum-mechanics","display_name":"Quantum mechanics","score":0.07248654961585999}],"concepts":[{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.7418731451034546},{"id":"https://openalex.org/C197055811","wikidata":"https://www.wikidata.org/wiki/Q207522","display_name":"Probability density function","level":2,"score":0.6610233783721924},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.619531512260437},{"id":"https://openalex.org/C51823790","wikidata":"https://www.wikidata.org/wiki/Q504353","display_name":"Greedy algorithm","level":2,"score":0.5105611085891724},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.4881911873817444},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.47494176030158997},{"id":"https://openalex.org/C61039578","wikidata":"https://www.wikidata.org/wiki/Q604279","display_name":"Dirac (video compression format)","level":3,"score":0.4676280617713928},{"id":"https://openalex.org/C129844170","wikidata":"https://www.wikidata.org/wiki/Q41299","display_name":"Quadratic equation","level":2,"score":0.45900461077690125},{"id":"https://openalex.org/C148764684","wikidata":"https://www.wikidata.org/wiki/Q621751","display_name":"Approximation algorithm","level":2,"score":0.453539103269577},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.42356839776039124},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.40497756004333496},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.3996945023536682},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.39909809827804565},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.22940102219581604},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.103658527135849},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.082816481590271},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.07248654961585999},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","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},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C186453547","wikidata":"https://www.wikidata.org/wiki/Q2126","display_name":"Neutrino","level":2,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/cdc.2007.4434778","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cdc.2007.4434778","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2007 46th IEEE Conference on Decision and Control","raw_type":"proceedings-article"},{"id":"pmh:oai:EVASTAR-Karlsruhe.de:1000034824","is_oa":false,"landing_page_url":"https://publikationen.bibliothek.kit.edu/1000034824","pdf_url":null,"source":{"id":"https://openalex.org/S4306401992","display_name":"Repository KITopen (Karlsruhe Institute of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I102335020","host_organization_name":"Karlsruhe Institute of Technology","host_organization_lineage":["https://openalex.org/I102335020"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"","raw_type":"doc-type:conferenceObject"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.304.8578","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.304.8578","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://isas.uka.de/Publikationen/CDC07_HanebeckSchrempf.pdf","raw_type":"text"},{"id":"doi:10.5445/ir/1000034824","is_oa":true,"landing_page_url":"https://doi.org/10.5445/ir/1000034824","pdf_url":null,"source":{"id":"https://openalex.org/S7407052948","display_name":"KITopen","issn_l":null,"issn":[],"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":"article-journal"}],"best_oa_location":{"id":"doi:10.5445/ir/1000034824","is_oa":true,"landing_page_url":"https://doi.org/10.5445/ir/1000034824","pdf_url":null,"source":{"id":"https://openalex.org/S7407052948","display_name":"KITopen","issn_l":null,"issn":[],"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":false,"raw_source_name":null,"raw_type":"article-journal"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1965555277","https://openalex.org/W2006515871","https://openalex.org/W2043253481","https://openalex.org/W2092407125","https://openalex.org/W2099502403","https://openalex.org/W2099867508","https://openalex.org/W2121075403","https://openalex.org/W2126736494","https://openalex.org/W2135906601","https://openalex.org/W2141162165","https://openalex.org/W2150744922","https://openalex.org/W2152767074","https://openalex.org/W2160337655","https://openalex.org/W6661333666"],"related_works":["https://openalex.org/W3204684126","https://openalex.org/W3117290964","https://openalex.org/W1594413663","https://openalex.org/W2045237525","https://openalex.org/W189401716","https://openalex.org/W2898570308","https://openalex.org/W2019216770","https://openalex.org/W2979334915","https://openalex.org/W2574250816","https://openalex.org/W2544904580"],"abstract_inverted_index":{"Greedy":[0],"procedures":[1],"for":[2,68,130,145],"suboptimal":[3],"Dirac":[4,69],"mixture":[5],"approximation":[6,154],"of":[7,111,122,128,150,160],"an":[8],"arbitrary":[9],"probability":[10],"density":[11,19,49],"function":[12],"are":[13,115],"proposed,":[14],"which":[15],"approach":[16,155],"the":[17,30,39,47,55,61,75,86,95,98,109,119,125,151,161],"desired":[18],"by":[20,45],"sequentially":[21],"adding":[22],"one":[23],"component":[24],"at":[25],"a":[26,35,58,79,132,138],"time.":[27],"Similar":[28],"to":[29,54,94,158],"batch":[31,96,163],"solutions":[32],"proposed":[33,152],"earlier,":[34],"distance":[36,59,83],"measure":[37,84],"between":[38,60,85],"corresponding":[40,48],"cumulative":[41],"distributions":[42],"is":[43,52,63,101,136,156],"minimized":[44],"selecting":[46],"parameters.":[50],"This":[51,71],"due":[53],"fact,":[56],"that":[57,159],"densities":[62],"typically":[64],"not":[65,137],"well":[66],"defined":[67],"mixtures.":[70],"paper":[72],"focuses":[73],"on":[74],"Cramer-von":[76],"Mises":[77],"distance,":[78],"weighted":[80],"integral":[81],"quadratic":[82],"true":[87],"distribution":[88],"and":[89,104,141],"its":[90],"approximation.":[91],"In":[92],"contrast":[93],"solutions,":[97],"computational":[99],"complexity":[100],"much":[102],"lower":[103],"grows":[105],"only":[106],"linearly":[107],"with":[108],"number":[110,121,127],"components.":[112],"Computational":[113],"savings":[114],"even":[116],"greater,":[117],"when":[118],"required":[120],"components,":[123],"e.g.,":[124],"minimum":[126],"components":[129],"achieving":[131],"given":[133],"quality":[134],"measure,":[135],"priori":[139],"known":[140],"must":[142],"be":[143],"searched":[144],"as":[146],"well.":[147],"The":[148],"performance":[149],"sequential":[153],"compared":[157],"optimal":[162],"solution.":[164]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2014,"cited_by_count":4},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":2}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
