{"id":"https://openalex.org/W2063567013","doi":"https://doi.org/10.1145/2582112.2582161","title":"Better \u03f5-Dependencies for Offline Approximate Nearest Neighbor Search, Euclidean Minimum Spanning Trees, and \u03f5-Kernels","display_name":"Better \u03f5-Dependencies for Offline Approximate Nearest Neighbor Search, Euclidean Minimum Spanning Trees, and \u03f5-Kernels","publication_year":2014,"publication_date":"2014-05-02","ids":{"openalex":"https://openalex.org/W2063567013","doi":"https://doi.org/10.1145/2582112.2582161","mag":"2063567013"},"language":"en","primary_location":{"id":"doi:10.1145/2582112.2582161","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2582112.2582161","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the thirtieth annual symposium on Computational geometry","raw_type":"proceedings-article"},"type":"conference-paper","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/A5022760571","display_name":"Sunil Arya","orcid":"https://orcid.org/0000-0003-0939-4192"},"institutions":[{"id":"https://openalex.org/I200769079","display_name":"Hong Kong University of Science and Technology","ror":"https://ror.org/00q4vv597","country_code":"HK","type":"education","lineage":["https://openalex.org/I200769079"]},{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Sunil Arya","raw_affiliation_strings":["Department of Computer Sci. & Eng., HKUST, Hong Kong","Department of Computer Sci. & Eng., HKUST, Hong Kong#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Sci. & Eng., HKUST, Hong Kong","institution_ids":["https://openalex.org/I200769079","https://openalex.org/I889458895"]},{"raw_affiliation_string":"Department of Computer Sci. & Eng., HKUST, Hong Kong#TAB#","institution_ids":["https://openalex.org/I200769079"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032955418","display_name":"Timothy M. Chan","orcid":"https://orcid.org/0000-0002-8093-0675"},"institutions":[{"id":"https://openalex.org/I151746483","display_name":"University of Waterloo","ror":"https://ror.org/01aff2v68","country_code":"CA","type":"education","lineage":["https://openalex.org/I151746483"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Timothy M. Chan","raw_affiliation_strings":["Cheriton School of Computer Science, University of Waterloo, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cheriton School of Computer Science, University of Waterloo, Canada","institution_ids":["https://openalex.org/I151746483"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"416","last_page":"425"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9991000294685364,"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/T11106","display_name":"Data Management and Algorithms","score":0.9991000294685364,"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/T10996","display_name":"Computational Geometry and Mesh Generation","score":0.9980999827384949,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"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":0.9952999949455261,"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/euclidean-space","display_name":"Euclidean space","score":0.6355518698692322},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.6241492033004761},{"id":"https://openalex.org/keywords/k-nearest-neighbors-algorithm","display_name":"k-nearest neighbors algorithm","score":0.609710693359375},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.6038146018981934},{"id":"https://openalex.org/keywords/euclidean-geometry","display_name":"Euclidean geometry","score":0.5837128162384033},{"id":"https://openalex.org/keywords/euclidean-distance","display_name":"Euclidean distance","score":0.5311815738677979},{"id":"https://openalex.org/keywords/best-bin-first","display_name":"Best bin first","score":0.49814581871032715},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4724833369255066},{"id":"https://openalex.org/keywords/nearest-neighbor-search","display_name":"Nearest neighbor search","score":0.4614924192428589},{"id":"https://openalex.org/keywords/constant","display_name":"Constant (computer programming)","score":0.4479783773422241},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.44694021344184875},{"id":"https://openalex.org/keywords/minimum-spanning-tree","display_name":"Minimum spanning tree","score":0.42020082473754883},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4125629663467407},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.40839335322380066},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.16525831818580627}],"concepts":[{"id":"https://openalex.org/C186450821","wikidata":"https://www.wikidata.org/wiki/Q17295","display_name":"Euclidean space","level":2,"score":0.6355518698692322},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.6241492033004761},{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.609710693359375},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.6038146018981934},{"id":"https://openalex.org/C129782007","wikidata":"https://www.wikidata.org/wiki/Q162886","display_name":"Euclidean geometry","level":2,"score":0.5837128162384033},{"id":"https://openalex.org/C120174047","wikidata":"https://www.wikidata.org/wiki/Q847073","display_name":"Euclidean distance","level":2,"score":0.5311815738677979},{"id":"https://openalex.org/C161986146","wikidata":"https://www.wikidata.org/wiki/Q4896845","display_name":"Best bin first","level":3,"score":0.49814581871032715},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4724833369255066},{"id":"https://openalex.org/C116738811","wikidata":"https://www.wikidata.org/wiki/Q608751","display_name":"Nearest neighbor search","level":2,"score":0.4614924192428589},{"id":"https://openalex.org/C2777027219","wikidata":"https://www.wikidata.org/wiki/Q1284190","display_name":"Constant (computer programming)","level":2,"score":0.4479783773422241},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.44694021344184875},{"id":"https://openalex.org/C13743678","wikidata":"https://www.wikidata.org/wiki/Q240464","display_name":"Minimum spanning tree","level":2,"score":0.42020082473754883},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4125629663467407},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.40839335322380066},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.16525831818580627},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/2582112.2582161","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2582112.2582161","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the thirtieth annual symposium on Computational geometry","raw_type":"proceedings-article"},{"id":"pmh:oai:repository.hkust.edu.hk:1783.1-64974","is_oa":false,"landing_page_url":"http://lbdiscover.ust.hk/uresolver?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rfr_id=info:sid/HKUST:SPI&rft.genre=article&rft.issn=&rft.volume=&rft.issue=&rft.date=2014&rft.spage=416&rft.aulast=Arya&rft.aufirst=S.&rft.atitle=Better+%CE%B5-dependencies+for+offline+approximate+nearest+neighbor+search%2C+euclidean+minimum+spanning+trees%2C+and+%CE%B5-kernels&rft.title=Proceedings+of+the+Annual+Symposium+on+Computational+Geometry","pdf_url":null,"source":{"id":"https://openalex.org/S4306401796","display_name":"Rare & Special e-Zone (The Hong Kong University of Science and Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I200769079","host_organization_name":"Hong Kong University of Science and Technology","host_organization_lineage":["https://openalex.org/I200769079"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Conference paper"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W127380945","https://openalex.org/W596522316","https://openalex.org/W1577072106","https://openalex.org/W1647207848","https://openalex.org/W1963750764","https://openalex.org/W1968301997","https://openalex.org/W1970319631","https://openalex.org/W1981313592","https://openalex.org/W1986084080","https://openalex.org/W1992843866","https://openalex.org/W1996064221","https://openalex.org/W2001342485","https://openalex.org/W2007273639","https://openalex.org/W2024409132","https://openalex.org/W2027673602","https://openalex.org/W2028430839","https://openalex.org/W2037134555","https://openalex.org/W2054011861","https://openalex.org/W2054788982","https://openalex.org/W2083694582","https://openalex.org/W2086591901","https://openalex.org/W2094974501","https://openalex.org/W2098355410","https://openalex.org/W2101479644","https://openalex.org/W2119014534","https://openalex.org/W2120871456","https://openalex.org/W2147717514","https://openalex.org/W2152564789","https://openalex.org/W2158944832","https://openalex.org/W2161134633","https://openalex.org/W2218835040","https://openalex.org/W2427881153","https://openalex.org/W2952460245","https://openalex.org/W3020889619","https://openalex.org/W4242128187","https://openalex.org/W4248484045","https://openalex.org/W6638855557"],"related_works":["https://openalex.org/W2381195555","https://openalex.org/W4246757943","https://openalex.org/W2245581955","https://openalex.org/W2182477562","https://openalex.org/W1595303882","https://openalex.org/W1558159560","https://openalex.org/W2109424811","https://openalex.org/W2148008870","https://openalex.org/W3096071782","https://openalex.org/W2097149198"],"abstract_inverted_index":{"Recently,":[0],"Arya,":[1],"da":[2],"Fonseca,":[3],"and":[4,42,70],"Mount":[5],"[STOC":[6],"2011,":[7],"SODA":[8],"2012]":[9],"made":[10],"notable":[11],"progress":[12],"in":[13,17,29,35,82],"improving":[14],"the":[15,18,36,83,87],"\u03f5-dependencies":[16,34],"space/query-time":[19],"tradeoffs":[20],"for":[21,54,60],"(1":[22],"+":[23],"\u03f5)-factor":[24],"approximate":[25,65,71],"nearest":[26],"neighbor":[27],"search":[28],"fixed-dimensional":[30],"Euclidean":[31,72],"spaces.":[32],"However,":[33],"preprocessing":[37],"time":[38,85],"were":[39],"not":[40],"considered,":[41],"so":[43],"their":[44],"data":[45],"structures":[46],"cannot":[47],"be":[48],"used":[49],"to":[50],"derive":[51],"faster":[52],"algorithms":[53,59],"offline":[55],"proximity":[56],"problems.":[57],"Known":[58],"many":[61],"such":[62],"problems,":[63],"including":[64],"bichromatic":[66],"closest":[67],"pair":[68],"(BCP)":[69],"minimum":[73],"spanning":[74],"trees":[75],"(EMST),":[76],"typically":[77],"have":[78],"factors":[79],"near":[80],"(1/\u03f5)d/2\u00b1O(1)":[81],"running":[84],"when":[86],"dimension":[88],"d":[89],"is":[90],"a":[91],"constant.":[92]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":2},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}