{"id":"https://openalex.org/W1526394777","doi":"https://doi.org/10.1145/2736277.2741665","title":"Sequential Hypothesis Tests for Adaptive Locality Sensitive Hashing","display_name":"Sequential Hypothesis Tests for Adaptive Locality Sensitive Hashing","publication_year":2015,"publication_date":"2015-05-18","ids":{"openalex":"https://openalex.org/W1526394777","doi":"https://doi.org/10.1145/2736277.2741665","mag":"1526394777"},"language":"en","primary_location":{"id":"doi:10.1145/2736277.2741665","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2736277.2741665","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 24th International Conference on World Wide Web","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1412.3103","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Aniket Chakrabarti","orcid":null},"institutions":[{"id":"https://openalex.org/I52357470","display_name":"The Ohio State University","ror":"https://ror.org/00rs6vg23","country_code":"US","type":"education","lineage":["https://openalex.org/I52357470"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Aniket Chakrabarti","raw_affiliation_strings":["The Ohio State University, Columbus, OH, USA"],"affiliations":[{"raw_affiliation_string":"The Ohio State University, Columbus, OH, USA","institution_ids":["https://openalex.org/I52357470"]}]},{"author_position":"last","author":{"id":null,"display_name":"Srinivasan Parthasarathy","orcid":null},"institutions":[{"id":"https://openalex.org/I52357470","display_name":"The Ohio State University","ror":"https://ror.org/00rs6vg23","country_code":"US","type":"education","lineage":["https://openalex.org/I52357470"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Srinivasan Parthasarathy","raw_affiliation_strings":["The Ohio State University, Columbus, OH, USA"],"affiliations":[{"raw_affiliation_string":"The Ohio State University, Columbus, OH, USA","institution_ids":["https://openalex.org/I52357470"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I52357470"],"apc_list":null,"apc_paid":null,"fwci":1.1196,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.84012099,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"162","last_page":"172"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9998999834060669,"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/T11269","display_name":"Algorithms and Data Compression","score":0.986299991607666,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9847999811172485,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/locality-sensitive-hashing","display_name":"Locality-sensitive hashing","score":0.7639999985694885},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.7062000036239624},{"id":"https://openalex.org/keywords/speedup","display_name":"Speedup","score":0.6601999998092651},{"id":"https://openalex.org/keywords/nearest-neighbor-search","display_name":"Nearest neighbor search","score":0.5533999800682068},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5351999998092651},{"id":"https://openalex.org/keywords/hash-function","display_name":"Hash function","score":0.45350000262260437},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.43720000982284546},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.42809998989105225},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.4138000011444092}],"concepts":[{"id":"https://openalex.org/C74270461","wikidata":"https://www.wikidata.org/wiki/Q1625299","display_name":"Locality-sensitive hashing","level":4,"score":0.7639999985694885},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.7062000036239624},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.6601999998092651},{"id":"https://openalex.org/C116738811","wikidata":"https://www.wikidata.org/wiki/Q608751","display_name":"Nearest neighbor search","level":2,"score":0.5533999800682068},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5351999998092651},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.505299985408783},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4715000092983246},{"id":"https://openalex.org/C99138194","wikidata":"https://www.wikidata.org/wiki/Q183427","display_name":"Hash function","level":2,"score":0.45350000262260437},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.450300008058548},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.43720000982284546},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.42809998989105225},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.4138000011444092},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.3862999975681305},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.38350000977516174},{"id":"https://openalex.org/C2780762811","wikidata":"https://www.wikidata.org/wiki/Q1784941","display_name":"Cosine similarity","level":3,"score":0.37950000166893005},{"id":"https://openalex.org/C162376815","wikidata":"https://www.wikidata.org/wiki/Q2158281","display_name":"Frequentist inference","level":4,"score":0.3646000027656555},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35510000586509705},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3531000018119812},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35030001401901245},{"id":"https://openalex.org/C2778067643","wikidata":"https://www.wikidata.org/wiki/Q166507","display_name":"Interval (graph theory)","level":2,"score":0.33489999175071716},{"id":"https://openalex.org/C87431388","wikidata":"https://www.wikidata.org/wiki/Q2070573","display_name":"Perfect hash function","level":4,"score":0.3346000015735626},{"id":"https://openalex.org/C2779808786","wikidata":"https://www.wikidata.org/wiki/Q6664603","display_name":"Locality","level":2,"score":0.3125},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.3025999963283539},{"id":"https://openalex.org/C67388219","wikidata":"https://www.wikidata.org/wiki/Q207440","display_name":"Hash table","level":3,"score":0.29589998722076416},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.2892000079154968},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2766000032424927},{"id":"https://openalex.org/C2780757406","wikidata":"https://www.wikidata.org/wiki/Q465837","display_name":"Skyline","level":2,"score":0.26969999074935913},{"id":"https://openalex.org/C87007009","wikidata":"https://www.wikidata.org/wiki/Q210832","display_name":"Statistical hypothesis testing","level":2,"score":0.2687999904155731},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.26570001244544983},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.2583000063896179},{"id":"https://openalex.org/C311688","wikidata":"https://www.wikidata.org/wiki/Q2393193","display_name":"Time complexity","level":2,"score":0.2565999925136566},{"id":"https://openalex.org/C118930307","wikidata":"https://www.wikidata.org/wiki/Q600590","display_name":"Tuple","level":2,"score":0.2535000145435333}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/2736277.2741665","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2736277.2741665","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 24th International Conference on World Wide Web","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1412.3103","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1412.3103","pdf_url":"https://arxiv.org/pdf/1412.3103","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":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1412.3103","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1412.3103","pdf_url":"https://arxiv.org/pdf/1412.3103","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":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1963567985","https://openalex.org/W1964731129","https://openalex.org/W1990537115","https://openalex.org/W1991800036","https://openalex.org/W1997841190","https://openalex.org/W2012833704","https://openalex.org/W2065259291","https://openalex.org/W2074614635","https://openalex.org/W2085922539","https://openalex.org/W2097776316","https://openalex.org/W2101196063","https://openalex.org/W2115022330","https://openalex.org/W2122056984","https://openalex.org/W2147717514","https://openalex.org/W2150102617","https://openalex.org/W2156855109","https://openalex.org/W2162006472","https://openalex.org/W4210997624"],"related_works":[],"abstract_inverted_index":{"All":[0],"pairs":[1,22],"similarity":[2,27,35,103,124,174,246],"search":[3],"is":[4,13,18,44,83,120,126,153,163,171],"a":[5,8,29,33,168,189,221,282,292],"problem":[6,69,187],"where":[7,114,159,244],"set":[9],"of":[10,23,40,92],"data":[11,118,161],"objects":[12,24],"given":[14,34],"and":[15,60,65,73,90,122,138,173,192,233,267,270,295],"the":[16,38,68,87,100,110,116,149,156,185,242,264],"task":[17],"to":[19,49,70,105,134,176,241,248],"find":[20],"all":[21],"that":[25,206,272],"have":[26],"above":[28],"certain":[30],"threshold":[31],"for":[32,85,196,214],"measure-of-interest.":[36],"When":[37],"number":[39],"points":[41],"or":[42,202],"dimensionality":[43],"high,":[45],"standard":[46],"solutions":[47,53],"fail":[48],"scale":[50],"gracefully.":[51],"Approximate":[52],"such":[54,211],"as":[55],"Locality":[56],"Sensitive":[57],"Hashing":[58],"(LSH)":[59],"its":[61],"Bayesian":[62],"variants":[63,240,262,269],"(BayesLSH":[64],"BayesLSHLite)":[66],"alleviate":[67],"some":[71],"extent":[72],"provide":[74,139,275],"substantial":[75,140],"speedup":[76,141],"over":[77,279],"traditional":[78,293],"index":[79],"based":[80,229],"approaches.":[81],"BayesLSH":[82,157],"used":[84,133],"pruning":[86,216],"candidate":[88],"space":[89],"computation":[91,125],"approximate":[93,245],"similarity,":[94],"whereas":[95],"BayesLSHLite":[96,130],"can":[97,131,207,274],"only":[98,167],"prune":[99,136],"candidates,":[101],"but":[102],"needs":[104,247],"be":[106,132,177,208,249],"computed":[107,250],"exactly":[108],"on":[109,146,230],"original":[111],"data.":[112],"Thus":[113],"ever":[115],"explicit":[117,160],"representation":[119,162],"available":[121,172],"exact":[123],"not":[127,164],"too":[128,144],"expensive,":[129],"aggressively":[135],"candidates":[137,217],"without":[142],"losing":[143],"much":[145],"quality.":[147],"However,":[148],"loss":[150],"in":[151,155],"quality":[152],"higher":[154],"variant,":[158],"available,":[165],"rather":[166],"hash":[169],"sketch":[170],"has":[175],"estimated":[178],"approximately.":[179],"In":[180],"this":[181,231],"work":[182],"we":[183],"revisit":[184],"LSH":[186,212],"from":[188],"Frequentist":[190],"setting":[191],"formulate":[193],"sequential":[194,223,253],"tests":[195],"composite":[197],"hypothesis":[198],"(similarity":[199],"greater":[200],"than":[201,204,291,298],"less":[203],"threshold)":[205],"leveraged":[209],"by":[210],"algorithms":[213],"adaptively":[215],"aggressively.":[218],"We":[219,237,258],"propose":[220],"vanilla":[222],"probability":[224],"ratio":[225],"test":[226],"(SPRT)":[227],"approach":[228,284],"idea":[232],"two":[234],"novel":[235,261],"variants.":[236],"extend":[238],"these":[239,260],"case":[243],"using":[251],"fixed-width":[252],"confidence":[254],"interval":[255],"generation":[256],"technique.":[257],"compare":[259],"with":[263],"SPRT":[265,294],"variant":[266],"BayesLSH/Bayes-LSHLite":[268],"show":[271],"they":[273],"tighter":[276],"qualitative":[277],"guarantees":[278],"BayesLSH/BayesLSHLite":[280],"--":[281,285],"state-of-the-art":[283],"while":[286],"being":[287],"upto":[288],"2.1x":[289],"faster":[290,297],"8.8x":[296],"AllPairs.":[299]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":1}],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2016-06-24T00:00:00"}
