{"id":"https://openalex.org/W178120446","doi":"https://doi.org/10.1007/978-3-7908-2604-3_21","title":"Data Dependent Priors in PAC-Bayes Bounds","display_name":"Data Dependent Priors in PAC-Bayes Bounds","publication_year":2010,"publication_date":"2010-01-01","ids":{"openalex":"https://openalex.org/W178120446","doi":"https://doi.org/10.1007/978-3-7908-2604-3_21","mag":"178120446"},"language":"en","primary_location":{"id":"doi:10.1007/978-3-7908-2604-3_21","is_oa":false,"landing_page_url":"https://doi.org/10.1007/978-3-7908-2604-3_21","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of COMPSTAT'2010","raw_type":"book-chapter"},"type":"book-chapter","indexed_in":["crossref"],"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/A5047980012","display_name":"John Shawe\u2010Taylor","orcid":"https://orcid.org/0000-0002-2030-0073"},"institutions":[{"id":"https://openalex.org/I45129253","display_name":"University College London","ror":"https://ror.org/02jx3x895","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I45129253"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"John Shawe-Taylor","raw_affiliation_strings":["Dept. of Computer Science & CSML, University College London, London, WC1E 6BT, UK"],"affiliations":[{"raw_affiliation_string":"Dept. of Computer Science & CSML, University College London, London, WC1E 6BT, UK","institution_ids":["https://openalex.org/I45129253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026967773","display_name":"Emilio Parrado-Hern\u00e1ndez","orcid":"https://orcid.org/0000-0003-2146-2135"},"institutions":[{"id":"https://openalex.org/I50357001","display_name":"Universidad Carlos III de Madrid","ror":"https://ror.org/03ths8210","country_code":"ES","type":"education","lineage":["https://openalex.org/I50357001"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Emilio Parrado-Hern\u00e1ndez","raw_affiliation_strings":["Dept. of Signal Processing and Communications, University Carlos III of Madrid, Legan\u00e9s, 28911, Spain"],"affiliations":[{"raw_affiliation_string":"Dept. of Signal Processing and Communications, University Carlos III of Madrid, Legan\u00e9s, 28911, Spain","institution_ids":["https://openalex.org/I50357001"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5063382447","display_name":"Amiran Ambroladze","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Amiran Ambroladze","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5047980012"],"corresponding_institution_ids":["https://openalex.org/I45129253"],"apc_list":null,"apc_paid":null,"fwci":0.2825,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.5172968,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"231","last_page":"240"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9976000189781189,"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/T10320","display_name":"Neural Networks and Applications","score":0.9976000189781189,"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/T10057","display_name":"Face and Expression Recognition","score":0.9966999888420105,"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9965999722480774,"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/prior-probability","display_name":"Prior probability","score":0.8467652797698975},{"id":"https://openalex.org/keywords/bounding-overwatch","display_name":"Bounding overwatch","score":0.7642146944999695},{"id":"https://openalex.org/keywords/upper-and-lower-bounds","display_name":"Upper and lower bounds","score":0.6550115346908569},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.5558908581733704},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5386251211166382},{"id":"https://openalex.org/keywords/bayes-theorem","display_name":"Bayes' theorem","score":0.5267633199691772},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5065594911575317},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4734327793121338},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4702664315700531},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4446406066417694},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.43766531348228455},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.4255823791027069},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.418567419052124},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4181559681892395},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.3009762763977051},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.14619600772857666}],"concepts":[{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.8467652797698975},{"id":"https://openalex.org/C63584917","wikidata":"https://www.wikidata.org/wiki/Q333286","display_name":"Bounding overwatch","level":2,"score":0.7642146944999695},{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.6550115346908569},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5558908581733704},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5386251211166382},{"id":"https://openalex.org/C207201462","wikidata":"https://www.wikidata.org/wiki/Q182505","display_name":"Bayes' theorem","level":3,"score":0.5267633199691772},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5065594911575317},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4734327793121338},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4702664315700531},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4446406066417694},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.43766531348228455},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.4255823791027069},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.418567419052124},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4181559681892395},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.3009762763977051},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.14619600772857666},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1007/978-3-7908-2604-3_21","is_oa":false,"landing_page_url":"https://doi.org/10.1007/978-3-7908-2604-3_21","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of COMPSTAT'2010","raw_type":"book-chapter"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.422.8699","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.422.8699","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://eprints.pascal-network.org/archive/00006782/01/compstat.pdf","raw_type":"text"},{"id":"pmh:oai:eprints.ucl.ac.uk.OAI2:1443234","is_oa":false,"landing_page_url":"http://discovery.ucl.ac.uk/1443234/","pdf_url":null,"source":{"id":"https://openalex.org/S4306400024","display_name":"UCL Discovery (University College London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I45129253","host_organization_name":"University College London","host_organization_lineage":["https://openalex.org/I45129253"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"   Proceedings of COMPSTAT 2010 - 19th International Conference on Computational Statistics, Keynote, Invited and Contributed Papers     pp. 231-240.   (2010)      ","raw_type":"Article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W2084812512","https://openalex.org/W2087347434","https://openalex.org/W2106491486","https://openalex.org/W2112065930","https://openalex.org/W2116314036","https://openalex.org/W2170207925","https://openalex.org/W2990138404","https://openalex.org/W2999905431"],"related_works":["https://openalex.org/W2132137594","https://openalex.org/W2069783012","https://openalex.org/W2343819364","https://openalex.org/W2133205540","https://openalex.org/W2085967955","https://openalex.org/W4256335355","https://openalex.org/W3098612666","https://openalex.org/W2138867060","https://openalex.org/W2023859141","https://openalex.org/W2182290077"],"abstract_inverted_index":{"One":[0],"of":[1,5,12,17,46,49,79,86,98,113,150,160],"the":[2,10,13,27,39,47,62,87,96,99,101,110,114,122,135,151,173,178,186],"central":[3],"aims":[4,132],"Statistical":[6],"Learning":[7],"Theory":[8],"is":[9,36,116],"bounding":[11],"test":[14],"set":[15,104,159],"performance":[16],"classifiers":[18],"trained":[19],"with":[20],"i.i.d.":[21],"data.":[22,80],"For":[23],"Support":[24],"Vector":[25],"Machines":[26],"tightest":[28,63],"technique":[29],"for":[30],"assessing":[31],"this":[32],"so-called":[33],"generalisation":[34,143],"error":[35],"known":[37],"as":[38,137],"PAC-Bayes":[40,188],"theorem.":[41],"The":[42,58,154],"bound":[43,136,175],"holds":[44],"independently":[45],"choice":[48],"prior,":[50],"but":[51],"better":[52],"priors":[53,59],"lead":[54,195],"to":[55,61,65,120,191,196],"sharper":[56],"bounds.":[57],"leading":[60],"bounds":[64],"date":[66],"are":[67,73],"spherical":[68],"Gaussian":[69],"distributions":[70],"whose":[71,142],"means":[72],"determined":[74],"from":[75],"a":[76,91,106,128,138,158,165],"separate":[77,102],"subset":[78],"This":[81],"paper":[82],"gives":[83],"another":[84],"turn":[85],"screw":[88],"by":[89,164],"introducing":[90],"further":[92],"data":[93,103],"dependence":[94],"on":[95,177],"shape":[97],"prior:":[100],"determines":[105],"direction":[107],"along":[108],"which":[109],"covariance":[111],"matrix":[112],"prior":[115],"stretched":[117],"in":[118,148],"order":[119],"sharpen":[121],"bound.":[123,153],"In":[124],"addition,":[125],"we":[126],"present":[127],"classification":[129,161],"algorithm":[130],"that":[131],"at":[133],"minimizing":[134],"design":[139],"criterion":[140],"and":[141,194],"can":[144,181],"be":[145,182],"easily":[146],"analysed":[147],"terms":[149],"new":[152,174,179],"experimental":[155],"work":[156],"includes":[157],"tasks":[162],"preceded":[163],"bound-driven":[166],"model":[167],"selection.":[168],"These":[169],"experiments":[170],"illustrate":[171],"how":[172],"acting":[176],"classifier":[180],"much":[183],"tighter":[184],"than":[185],"original":[187],"Bound":[189],"applied":[190],"an":[192],"SVM,":[193],"more":[197],"accurate":[198],"classifiers.":[199]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
