{"id":"https://openalex.org/W2982235755","doi":"https://doi.org/10.1109/icassp40776.2020.9054735","title":"Approximate Bayesian Computation with the Sliced-Wasserstein Distance","display_name":"Approximate Bayesian Computation with the Sliced-Wasserstein Distance","publication_year":2020,"publication_date":"2020-04-09","ids":{"openalex":"https://openalex.org/W2982235755","doi":"https://doi.org/10.1109/icassp40776.2020.9054735","mag":"2982235755"},"language":"en","primary_location":{"id":"doi:10.1109/icassp40776.2020.9054735","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9054735","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1910.12815","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5015712624","display_name":"Kimia Nadjahi","orcid":null},"institutions":[{"id":"https://openalex.org/I12356871","display_name":"T\u00e9l\u00e9com Paris","ror":"https://ror.org/01naq7912","country_code":"FR","type":"education","lineage":["https://openalex.org/I12356871","https://openalex.org/I205703379","https://openalex.org/I4210145102"]},{"id":"https://openalex.org/I2802330208","display_name":"Statistics Belgium","ror":"https://ror.org/0246a9012","country_code":"BE","type":"government","lineage":["https://openalex.org/I2802330208","https://openalex.org/I4210095879"]},{"id":"https://openalex.org/I4210165912","display_name":"Laboratoire Traitement et Communication de l\u2019Information","ror":"https://ror.org/057er4c39","country_code":"FR","type":"facility","lineage":["https://openalex.org/I12356871","https://openalex.org/I205703379","https://openalex.org/I4210145102","https://openalex.org/I4210165912"]}],"countries":["BE","FR"],"is_corresponding":true,"raw_author_name":"Kimia Nadjahi","raw_affiliation_strings":["LTCI, T\u00e9l\u00e9com Paris, Institut Polytechnique de Paris, France","Laboratoire Traitement et Communication de l'Information","D\u00e9partement Images, Donn\u00e9es, Signal","T\u00e9l\u00e9com ParisTech","Signal, Statistique et Apprentissage"],"affiliations":[{"raw_affiliation_string":"LTCI, T\u00e9l\u00e9com Paris, Institut Polytechnique de Paris, France","institution_ids":["https://openalex.org/I4210165912","https://openalex.org/I12356871"]},{"raw_affiliation_string":"Laboratoire Traitement et Communication de l'Information","institution_ids":["https://openalex.org/I4210165912"]},{"raw_affiliation_string":"D\u00e9partement Images, Donn\u00e9es, Signal","institution_ids":[]},{"raw_affiliation_string":"T\u00e9l\u00e9com ParisTech","institution_ids":["https://openalex.org/I12356871"]},{"raw_affiliation_string":"Signal, Statistique et Apprentissage","institution_ids":["https://openalex.org/I2802330208"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050614717","display_name":"Valentin De Bortoli","orcid":"https://orcid.org/0000-0002-7163-5391"},"institutions":[{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"government","lineage":["https://openalex.org/I1294671590"]},{"id":"https://openalex.org/I4210150889","display_name":"Center for MathematicaL studies and their Applications","ror":"https://ror.org/05pabaz56","country_code":"FR","type":"facility","lineage":["https://openalex.org/I11559806","https://openalex.org/I1294671590","https://openalex.org/I277688954","https://openalex.org/I4210141950","https://openalex.org/I4210150889"]},{"id":"https://openalex.org/I277688954","display_name":"Universit\u00e9 Paris-Saclay","ror":"https://ror.org/03xjwb503","country_code":"FR","type":"education","lineage":["https://openalex.org/I277688954"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Valentin De Bortoli","raw_affiliation_strings":["CMLA, \u00c9cole normale sup\u00e9rieure Paris-Saclay, CNRS, Universit\u00e9 Paris-Saclay, France","Centre de Math\u00e9matiques et de Leurs Applications"],"affiliations":[{"raw_affiliation_string":"CMLA, \u00c9cole normale sup\u00e9rieure Paris-Saclay, CNRS, Universit\u00e9 Paris-Saclay, France","institution_ids":["https://openalex.org/I277688954","https://openalex.org/I1294671590"]},{"raw_affiliation_string":"Centre de Math\u00e9matiques et de Leurs Applications","institution_ids":["https://openalex.org/I4210150889"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036096413","display_name":"Alain Durmus","orcid":"https://orcid.org/0000-0002-2086-8611"},"institutions":[{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"government","lineage":["https://openalex.org/I1294671590"]},{"id":"https://openalex.org/I277688954","display_name":"Universit\u00e9 Paris-Saclay","ror":"https://ror.org/03xjwb503","country_code":"FR","type":"education","lineage":["https://openalex.org/I277688954"]},{"id":"https://openalex.org/I4210150889","display_name":"Center for MathematicaL studies and their Applications","ror":"https://ror.org/05pabaz56","country_code":"FR","type":"facility","lineage":["https://openalex.org/I11559806","https://openalex.org/I1294671590","https://openalex.org/I277688954","https://openalex.org/I4210141950","https://openalex.org/I4210150889"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Alain Durmus","raw_affiliation_strings":["CMLA, \u00c9cole normale sup\u00e9rieure Paris-Saclay, CNRS, Universit\u00e9 Paris-Saclay, France","Centre de Math\u00e9matiques et de Leurs Applications"],"affiliations":[{"raw_affiliation_string":"CMLA, \u00c9cole normale sup\u00e9rieure Paris-Saclay, CNRS, Universit\u00e9 Paris-Saclay, France","institution_ids":["https://openalex.org/I277688954","https://openalex.org/I1294671590"]},{"raw_affiliation_string":"Centre de Math\u00e9matiques et de Leurs Applications","institution_ids":["https://openalex.org/I4210150889"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028865449","display_name":"Roland Badeau","orcid":"https://orcid.org/0000-0002-9630-6877"},"institutions":[{"id":"https://openalex.org/I12356871","display_name":"T\u00e9l\u00e9com Paris","ror":"https://ror.org/01naq7912","country_code":"FR","type":"education","lineage":["https://openalex.org/I12356871","https://openalex.org/I205703379","https://openalex.org/I4210145102"]},{"id":"https://openalex.org/I2802330208","display_name":"Statistics Belgium","ror":"https://ror.org/0246a9012","country_code":"BE","type":"government","lineage":["https://openalex.org/I2802330208","https://openalex.org/I4210095879"]},{"id":"https://openalex.org/I4210165912","display_name":"Laboratoire Traitement et Communication de l\u2019Information","ror":"https://ror.org/057er4c39","country_code":"FR","type":"facility","lineage":["https://openalex.org/I12356871","https://openalex.org/I205703379","https://openalex.org/I4210145102","https://openalex.org/I4210165912"]}],"countries":["BE","FR"],"is_corresponding":false,"raw_author_name":"Roland Badeau","raw_affiliation_strings":["LTCI, T\u00e9l\u00e9com Paris, Institut Polytechnique de Paris, France","Signal, Statistique et Apprentissage","Laboratoire Traitement et Communication de l'Information","T\u00e9l\u00e9com ParisTech","D\u00e9partement Images, Donn\u00e9es, Signal"],"affiliations":[{"raw_affiliation_string":"LTCI, T\u00e9l\u00e9com Paris, Institut Polytechnique de Paris, France","institution_ids":["https://openalex.org/I4210165912","https://openalex.org/I12356871"]},{"raw_affiliation_string":"Signal, Statistique et Apprentissage","institution_ids":["https://openalex.org/I2802330208"]},{"raw_affiliation_string":"Laboratoire Traitement et Communication de l'Information","institution_ids":["https://openalex.org/I4210165912"]},{"raw_affiliation_string":"T\u00e9l\u00e9com ParisTech","institution_ids":["https://openalex.org/I12356871"]},{"raw_affiliation_string":"D\u00e9partement Images, Donn\u00e9es, Signal","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053326908","display_name":"Umut \u015eim\u015fekli","orcid":null},"institutions":[{"id":"https://openalex.org/I2802330208","display_name":"Statistics Belgium","ror":"https://ror.org/0246a9012","country_code":"BE","type":"government","lineage":["https://openalex.org/I2802330208","https://openalex.org/I4210095879"]},{"id":"https://openalex.org/I12356871","display_name":"T\u00e9l\u00e9com Paris","ror":"https://ror.org/01naq7912","country_code":"FR","type":"education","lineage":["https://openalex.org/I12356871","https://openalex.org/I205703379","https://openalex.org/I4210145102"]},{"id":"https://openalex.org/I4210165912","display_name":"Laboratoire Traitement et Communication de l\u2019Information","ror":"https://ror.org/057er4c39","country_code":"FR","type":"facility","lineage":["https://openalex.org/I12356871","https://openalex.org/I205703379","https://openalex.org/I4210145102","https://openalex.org/I4210165912"]}],"countries":["BE","FR"],"is_corresponding":false,"raw_author_name":"Umut Simsekli","raw_affiliation_strings":["LTCI, T\u00e9l\u00e9com Paris, Institut Polytechnique de Paris, France","T\u00e9l\u00e9com ParisTech","Laboratoire Traitement et Communication de l'Information","Signal, Statistique et Apprentissage","D\u00e9partement Images, Donn\u00e9es, Signal"],"affiliations":[{"raw_affiliation_string":"LTCI, T\u00e9l\u00e9com Paris, Institut Polytechnique de Paris, France","institution_ids":["https://openalex.org/I4210165912","https://openalex.org/I12356871"]},{"raw_affiliation_string":"T\u00e9l\u00e9com ParisTech","institution_ids":["https://openalex.org/I12356871"]},{"raw_affiliation_string":"Laboratoire Traitement et Communication de l'Information","institution_ids":["https://openalex.org/I4210165912"]},{"raw_affiliation_string":"Signal, Statistique et Apprentissage","institution_ids":["https://openalex.org/I2802330208"]},{"raw_affiliation_string":"D\u00e9partement Images, Donn\u00e9es, Signal","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5015712624"],"corresponding_institution_ids":["https://openalex.org/I12356871","https://openalex.org/I2802330208","https://openalex.org/I4210165912"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.01486552,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"51","issue":null,"first_page":"5470","last_page":"5474"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12056","display_name":"Markov Chains and Monte Carlo Methods","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12056","display_name":"Markov Chains and Monte Carlo Methods","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"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/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9825000166893005,"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":0.9799000024795532,"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/computation","display_name":"Computation","score":0.7071835994720459},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6440930366516113},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.6051650643348694},{"id":"https://openalex.org/keywords/approximate-bayesian-computation","display_name":"Approximate Bayesian computation","score":0.5128729343414307},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4098471403121948},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3622991442680359},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.31707099080085754},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.29958826303482056}],"concepts":[{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.7071835994720459},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6440930366516113},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.6051650643348694},{"id":"https://openalex.org/C2779377595","wikidata":"https://www.wikidata.org/wiki/Q21045424","display_name":"Approximate Bayesian computation","level":3,"score":0.5128729343414307},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4098471403121948},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3622991442680359},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.31707099080085754},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.29958826303482056},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.0}],"mesh":[],"locations_count":6,"locations":[{"id":"doi:10.1109/icassp40776.2020.9054735","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9054735","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1910.12815","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1910.12815","pdf_url":"https://arxiv.org/pdf/1910.12815","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"pmh:oai:HAL:hal-02457063v1","is_oa":false,"landing_page_url":"https://telecom-paris.hal.science/hal-02457063","pdf_url":null,"source":{"id":"https://openalex.org/S4406922461","display_name":"SPIRE - Sciences Po Institutional REpository","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"45th International Conference on Acoustics, Speech, and Signal Processing, May 2020, Barcelona, Spain. &#x27E8;10.1109/icassp40776.2020.9054735&#x27E9;","raw_type":"Conference papers"},{"id":"pmh:oai:HAL:hal-03945515v1","is_oa":false,"landing_page_url":"https://hal.science/hal-03945515","pdf_url":null,"source":{"id":"https://openalex.org/S4406922454","display_name":"SPIRE - Sciences Po Institutional REpository","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2022","raw_type":"Preprints, Working Papers, ..."},{"id":"doi:10.48550/arxiv.1910.12815","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1910.12815","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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"},{"id":"doi:10.17023/s1gf-2t43","is_oa":true,"landing_page_url":"https://doi.org/10.17023/s1gf-2t43","pdf_url":null,"source":{"id":"https://openalex.org/S7407051697","display_name":"IEEE RESOURCE CENTERS","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"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1910.12815","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1910.12815","pdf_url":"https://arxiv.org/pdf/1910.12815","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W385466589","https://openalex.org/W786520459","https://openalex.org/W1594863551","https://openalex.org/W1639961155","https://openalex.org/W1793259860","https://openalex.org/W1973099219","https://openalex.org/W2019106840","https://openalex.org/W2092124742","https://openalex.org/W2097073572","https://openalex.org/W2116416291","https://openalex.org/W2121927366","https://openalex.org/W2152246075","https://openalex.org/W2494636976","https://openalex.org/W2788616582","https://openalex.org/W2793477525","https://openalex.org/W2798792107","https://openalex.org/W2907366006","https://openalex.org/W2916041869","https://openalex.org/W2949631852","https://openalex.org/W2956015785","https://openalex.org/W2962903918","https://openalex.org/W2963297889","https://openalex.org/W2963398989","https://openalex.org/W2963506208","https://openalex.org/W2970112944","https://openalex.org/W2970311603","https://openalex.org/W2973214398","https://openalex.org/W2979557588","https://openalex.org/W3124277137","https://openalex.org/W6622541878","https://openalex.org/W6693409169","https://openalex.org/W6748321574","https://openalex.org/W6750836980","https://openalex.org/W6752842830","https://openalex.org/W6757867572","https://openalex.org/W6759401939","https://openalex.org/W6765076167"],"related_works":["https://openalex.org/W3124497799","https://openalex.org/W2226294016","https://openalex.org/W3047807024","https://openalex.org/W3014258782","https://openalex.org/W4241947739","https://openalex.org/W2788616582","https://openalex.org/W24509564","https://openalex.org/W2015480483","https://openalex.org/W2113759402","https://openalex.org/W2949074946"],"abstract_inverted_index":{"Approximate":[0],"Bayesian":[1],"Computation":[2],"(ABC)":[3],"is":[4],"a":[5,51,102],"popular":[6],"method":[7],"for":[8,28],"approximate":[9,22],"inference":[10],"in":[11,38],"generative":[12],"models":[13],"with":[14],"intractable":[15],"but":[16,87],"easy-to-sample":[17],"likelihood.":[18],"It":[19],"constructs":[20],"an":[21,143],"posterior":[23],"distribution":[24],"by":[25],"finding":[26],"parameters":[27],"which":[29,55,115],"the":[30,36,61,64,77,80,93,96,112,128],"simulated":[31],"data":[32,141],"are":[33,45],"close":[34],"to":[35,59,92],"observations":[37],"terms":[39],"of":[40,53,63,98,131],"summary":[41],"statistics.":[42],"These":[43],"statistics":[44],"defined":[46],"beforehand":[47],"and":[48,75,109,119,134,142],"might":[49],"induce":[50],"loss":[52],"information,":[54],"has":[56,71,116],"been":[57,72],"shown":[58],"deteriorate":[60],"quality":[62],"approximation.":[65],"To":[66],"overcome":[67],"this":[68],"problem,":[69],"Wasserstein-ABC":[70],"recently":[73],"proposed,":[74],"compares":[76],"datasets":[78],"via":[79],"Wasserstein":[81],"distance":[82],"between":[83],"their":[84],"empirical":[85],"distributions,":[86],"does":[88],"not":[89],"scale":[90],"well":[91],"dimension":[94],"or":[95],"number":[97],"samples.":[99],"We":[100,122],"propose":[101],"new":[103],"ABC":[104,108],"technique,":[105],"called":[106],"Sliced-Wasserstein":[107,113],"based":[110],"on":[111,139],"distance,":[114],"better":[117],"computational":[118],"statistical":[120],"properties.":[121],"derive":[123],"two":[124],"theoretical":[125],"results":[126],"showing":[127],"asymptotical":[129],"consistency":[130],"our":[132],"approach,":[133],"we":[135],"illustrate":[136],"its":[137],"advantages":[138],"synthetic":[140],"image":[144],"denoising":[145],"task.":[146]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2019-11-01T00:00:00"}
