{"id":"https://openalex.org/W4402112563","doi":"https://doi.org/10.1007/s10618-024-01063-6","title":"Efficient learning with projected histograms","display_name":"Efficient learning with projected histograms","publication_year":2024,"publication_date":"2024-09-01","ids":{"openalex":"https://openalex.org/W4402112563","doi":"https://doi.org/10.1007/s10618-024-01063-6"},"language":"en","primary_location":{"id":"doi:10.1007/s10618-024-01063-6","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10618-024-01063-6","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10618-024-01063-6.pdf","source":{"id":"https://openalex.org/S121920818","display_name":"Data Mining and Knowledge Discovery","issn_l":"1384-5810","issn":["1384-5810","1573-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Data Mining and Knowledge Discovery","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s10618-024-01063-6.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5113361577","display_name":"Zhanliang Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I79619799","display_name":"University of Birmingham","ror":"https://ror.org/03angcq70","country_code":"GB","type":"education","lineage":["https://openalex.org/I79619799"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Zhanliang Huang","raw_affiliation_strings":["School of Computer Science, University of Birmingham, Edgbaston, Birmingham, B15 2TT, Birmingham, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Birmingham, Edgbaston, Birmingham, B15 2TT, Birmingham, UK","institution_ids":["https://openalex.org/I79619799"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001135130","display_name":"Ata Kab\u00e1n","orcid":"https://orcid.org/0000-0003-3733-7064"},"institutions":[{"id":"https://openalex.org/I79619799","display_name":"University of Birmingham","ror":"https://ror.org/03angcq70","country_code":"GB","type":"education","lineage":["https://openalex.org/I79619799"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Ata Kab\u00e1n","raw_affiliation_strings":["School of Computer Science, University of Birmingham, Edgbaston, Birmingham, B15 2TT, Birmingham, UK"],"raw_orcid":"https://orcid.org/0000-0003-3733-7064","affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Birmingham, Edgbaston, Birmingham, B15 2TT, Birmingham, UK","institution_ids":["https://openalex.org/I79619799"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064091476","display_name":"Henry W. J. Reeve","orcid":"https://orcid.org/0000-0002-5801-2413"},"institutions":[{"id":"https://openalex.org/I36234482","display_name":"University of Bristol","ror":"https://ror.org/0524sp257","country_code":"GB","type":"education","lineage":["https://openalex.org/I36234482"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Henry Reeve","raw_affiliation_strings":["School of Mathematics, University of Bristol, Woodland Road, Bristol, BS8 1UG, Bristol, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematics, University of Bristol, Woodland Road, Bristol, BS8 1UG, Bristol, UK","institution_ids":["https://openalex.org/I36234482"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5001135130"],"corresponding_institution_ids":["https://openalex.org/I79619799"],"apc_list":{"value":3090,"currency":"USD","value_usd":3090},"apc_paid":{"value":3090,"currency":"USD","value_usd":3090},"fwci":0.241,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.56685636,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":94},"biblio":{"volume":"38","issue":"6","first_page":"3948","last_page":"4000"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12536","display_name":"Topological and Geometric Data Analysis","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T12536","display_name":"Topological and Geometric Data Analysis","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9890999794006348,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9864000082015991,"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/computer-science","display_name":"Computer science","score":0.6283516883850098},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5302873253822327},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.45010656118392944}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6283516883850098},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5302873253822327},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.45010656118392944},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1007/s10618-024-01063-6","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10618-024-01063-6","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10618-024-01063-6.pdf","source":{"id":"https://openalex.org/S121920818","display_name":"Data Mining and Knowledge Discovery","issn_l":"1384-5810","issn":["1384-5810","1573-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Data Mining and Knowledge Discovery","raw_type":"journal-article"},{"id":"pmh:oai:pure.atira.dk:openaire_cris_publications/6afab6ff-2534-432a-a2bd-822027b74433","is_oa":true,"landing_page_url":"https://research.birmingham.ac.uk/en/publications/6afab6ff-2534-432a-a2bd-822027b74433","pdf_url":null,"source":{"id":"https://openalex.org/S4306402634","display_name":"University of Birmingham Research Portal (University of Birmingham)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I79619799","host_organization_name":"University of Birmingham","host_organization_lineage":["https://openalex.org/I79619799"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Huang , Z , Kaban , A & Reeve , H 2024 , ' Efficient Learning with Projected Histograms ' , Data Mining and Knowledge Discovery . https://doi.org/10.1007/s10618-024-01063-6","raw_type":"article"},{"id":"pmh:oai:pure.atira.dk:publications/6afab6ff-2534-432a-a2bd-822027b74433","is_oa":true,"landing_page_url":"https://research.birmingham.ac.uk/files/237594466/s10618-024-01063-6.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306402634","display_name":"University of Birmingham Research Portal (University of Birmingham)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I79619799","host_organization_name":"University of Birmingham","host_organization_lineage":["https://openalex.org/I79619799"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Huang , Z , Kaban , A & Reeve , H 2024 , ' Efficient Learning with Projected Histograms ' , Data Mining and Knowledge Discovery . https://doi.org/10.1007/s10618-024-01063-6","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1007/s10618-024-01063-6","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10618-024-01063-6","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10618-024-01063-6.pdf","source":{"id":"https://openalex.org/S121920818","display_name":"Data Mining and Knowledge Discovery","issn_l":"1384-5810","issn":["1384-5810","1573-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Data Mining and Knowledge Discovery","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Partnerships for the goals","id":"https://metadata.un.org/sdg/17","score":0.4699999988079071}],"awards":[{"id":"https://openalex.org/G436636981","display_name":"FORGING: Fortuitous Geometries and Compressive Learning","funder_award_id":"EP/P004245/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G909344087","display_name":null,"funder_award_id":"EP/P004245/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"}],"funders":[{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4402112563.pdf","grobid_xml":"https://content.openalex.org/works/W4402112563.grobid-xml"},"referenced_works_count":37,"referenced_works":["https://openalex.org/W98731650","https://openalex.org/W1564947197","https://openalex.org/W1602085912","https://openalex.org/W1726806267","https://openalex.org/W1885794093","https://openalex.org/W1974973278","https://openalex.org/W1979593580","https://openalex.org/W1986736933","https://openalex.org/W1991669689","https://openalex.org/W1996437515","https://openalex.org/W2024930473","https://openalex.org/W2028584480","https://openalex.org/W2048092465","https://openalex.org/W2074006684","https://openalex.org/W2080446417","https://openalex.org/W2088658556","https://openalex.org/W2089497633","https://openalex.org/W2096870293","https://openalex.org/W2113385666","https://openalex.org/W2157878484","https://openalex.org/W2288884963","https://openalex.org/W2293291360","https://openalex.org/W2739273495","https://openalex.org/W2787676258","https://openalex.org/W2964343357","https://openalex.org/W3035174002","https://openalex.org/W3101056443","https://openalex.org/W3104165014","https://openalex.org/W3147249397","https://openalex.org/W3157962441","https://openalex.org/W4236362309","https://openalex.org/W4247922705","https://openalex.org/W4393187309","https://openalex.org/W6600603392","https://openalex.org/W6605731050","https://openalex.org/W6817422950","https://openalex.org/W6830682299"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052","https://openalex.org/W2382290278","https://openalex.org/W4395014643"],"abstract_inverted_index":{"Abstract":[0],"High":[1],"dimensional":[2],"learning":[3,17],"is":[4,35,172],"a":[5,56,73,118,154],"perennial":[6],"problem":[7],"due":[8],"to":[9,43,46,60,85,105,174],"challenges":[10],"posed":[11],"by":[12,38],"the":[13,48,79,93,106,129,134,138,149,179,182],"\u201ccurse":[14],"of":[15,63,78,88,132,148,160,162,178,184],"dimensionality\u201d;":[16],"typically":[18],"demands":[19],"more":[20,26],"computing":[21],"resources":[22],"as":[23,25],"well":[24],"training":[27,110],"data.":[28,80],"In":[29,51],"differentially":[30,122],"private":[31,123,215],"(DP)":[32,124],"settings,":[33,167],"this":[34,52],"further":[36,127],"exacerbated":[37],"noise":[39,185],"that":[40,126,169,204],"needs":[41],"adding":[42],"each":[44],"dimension":[45],"achieve":[47,207],"required":[49,186],"privacy.":[50],"paper,":[53],"we":[54],"present":[55,153],"surprisingly":[57],"simple":[58],"approach":[59,82,171],"address":[61],"all":[62],"these":[64],"concerns":[65],"at":[66],"once,":[67],"based":[68,140],"on":[69,72],"histograms":[70],"constructed":[71],"low-dimensional":[74,90,176],"random":[75],"projection":[76],"(RP)":[77],"Our":[81],"exploits":[83,128],"RP":[84,139],"take":[86],"advantage":[87],"hidden":[89],"structures":[91],"in":[92,144,165,211],"data,":[94,180],"yielding":[95],"both":[96,133,212],"computational":[97],"efficiency,":[98],"and":[99,137,156,189,202,214],"improved":[100],"error":[101],"convergence":[102],"with":[103],"respect":[104],"sample":[107],"size\u2014whereby":[108],"less":[109],"data":[111],"suffice":[112],"for":[113,120,187],"learning.":[114],"We":[115,152,196],"also":[116,197],"propose":[117],"variant":[119],"efficient":[121,146],"classification":[125,209],"data-oblivious":[130],"nature":[131],"histogram":[135],"construction":[136],"dimensionality":[141],"reduction,":[142],"resulting":[143],"an":[145],"management":[147],"privacy":[150],"budget.":[151],"detailed":[155],"rigorous":[157],"theoretical":[158],"analysis":[159],"generalisation":[161,192],"our":[163,170,199,205],"algorithms":[164,206],"several":[166],"showing":[168],"able":[173],"exploit":[175],"structure":[177],"ameliorates":[181],"ill-effects":[183],"privacy,":[188],"has":[190],"good":[191],"under":[193],"minimal":[194],"conditions.":[195],"corroborate":[198],"findings":[200],"experimentally,":[201],"demonstrate":[203],"competitive":[208],"accuracy":[210],"non-private":[213],"settings.":[216]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-08-28T12:50:07.497085","created_date":"2025-10-10T00:00:00"}
