{"id":"https://openalex.org/W2735058673","doi":"https://doi.org/10.1109/ijcnn.2017.7966218","title":"Improved maximum inner product search with better theoretical guarantees","display_name":"Improved maximum inner product search with better theoretical guarantees","publication_year":2017,"publication_date":"2017-05-01","ids":{"openalex":"https://openalex.org/W2735058673","doi":"https://doi.org/10.1109/ijcnn.2017.7966218","mag":"2735058673"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2017.7966218","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2017.7966218","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"article","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/A5084292336","display_name":"Omid Keivani","orcid":null},"institutions":[{"id":"https://openalex.org/I39587148","display_name":"Wichita State University","ror":"https://ror.org/00c4e7y75","country_code":"US","type":"education","lineage":["https://openalex.org/I39587148"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Omid Keivani","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, Wichita State University, Wichita, KS, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, Wichita State University, Wichita, KS, USA","institution_ids":["https://openalex.org/I39587148"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103257165","display_name":"K. P. Sinha","orcid":"https://orcid.org/0000-0002-0025-5754"},"institutions":[{"id":"https://openalex.org/I39587148","display_name":"Wichita State University","ror":"https://ror.org/00c4e7y75","country_code":"US","type":"education","lineage":["https://openalex.org/I39587148"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kaushik Sinha","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, Wichita State University, Wichita, KS, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, Wichita State University, Wichita, KS, USA","institution_ids":["https://openalex.org/I39587148"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5089095944","display_name":"Parikshit Ram","orcid":"https://orcid.org/0000-0002-9456-029X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Parikshit Ram","raw_affiliation_strings":["Skytree, Inc., Atlanta, GA, USA"],"affiliations":[{"raw_affiliation_string":"Skytree, Inc., Atlanta, GA, USA","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5084292336"],"corresponding_institution_ids":["https://openalex.org/I39587148"],"apc_list":null,"apc_paid":null,"fwci":0.5543,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.75925608,"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":"2927","last_page":"2934"},"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":0.9993000030517578,"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":0.9993000030517578,"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/T11106","display_name":"Data Management and Algorithms","score":0.9943000078201294,"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/T12016","display_name":"Web Data Mining and Analysis","score":0.9717000126838684,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.7420668601989746},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.5287570357322693},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.5280110239982605},{"id":"https://openalex.org/keywords/locality-sensitive-hashing","display_name":"Locality-sensitive hashing","score":0.5056624412536621},{"id":"https://openalex.org/keywords/partition","display_name":"Partition (number theory)","score":0.5000169277191162},{"id":"https://openalex.org/keywords/product","display_name":"Product (mathematics)","score":0.43776506185531616},{"id":"https://openalex.org/keywords/locality","display_name":"Locality","score":0.42032328248023987},{"id":"https://openalex.org/keywords/usability","display_name":"Usability","score":0.41935139894485474},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.4128417372703552},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.38284602761268616},{"id":"https://openalex.org/keywords/hash-function","display_name":"Hash function","score":0.2998392581939697},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2894919514656067},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.282970130443573},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17734289169311523},{"id":"https://openalex.org/keywords/hash-table","display_name":"Hash table","score":0.09845727682113647}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7420668601989746},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.5287570357322693},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.5280110239982605},{"id":"https://openalex.org/C74270461","wikidata":"https://www.wikidata.org/wiki/Q1625299","display_name":"Locality-sensitive hashing","level":4,"score":0.5056624412536621},{"id":"https://openalex.org/C42812","wikidata":"https://www.wikidata.org/wiki/Q1082910","display_name":"Partition (number theory)","level":2,"score":0.5000169277191162},{"id":"https://openalex.org/C90673727","wikidata":"https://www.wikidata.org/wiki/Q901718","display_name":"Product (mathematics)","level":2,"score":0.43776506185531616},{"id":"https://openalex.org/C2779808786","wikidata":"https://www.wikidata.org/wiki/Q6664603","display_name":"Locality","level":2,"score":0.42032328248023987},{"id":"https://openalex.org/C170130773","wikidata":"https://www.wikidata.org/wiki/Q216378","display_name":"Usability","level":2,"score":0.41935139894485474},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.4128417372703552},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.38284602761268616},{"id":"https://openalex.org/C99138194","wikidata":"https://www.wikidata.org/wiki/Q183427","display_name":"Hash function","level":2,"score":0.2998392581939697},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2894919514656067},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.282970130443573},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17734289169311523},{"id":"https://openalex.org/C67388219","wikidata":"https://www.wikidata.org/wiki/Q207440","display_name":"Hash table","level":3,"score":0.09845727682113647},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/ijcnn.2017.7966218","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2017.7966218","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},{"id":"pmh:oai:soar.wichita.edu:10057/14865","is_oa":false,"landing_page_url":"http://hdl.handle.net/10057/14865","pdf_url":null,"source":{"id":"https://openalex.org/S4306401479","display_name":"Holmes Museum Of Anthropology (Wichita State University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I39587148","host_organization_name":"Wichita State University","host_organization_lineage":["https://openalex.org/I39587148"],"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":[{"score":0.4699999988079071,"id":"https://metadata.un.org/sdg/8","display_name":"Decent work and economic growth"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1502916507","https://openalex.org/W1575370549","https://openalex.org/W1591023622","https://openalex.org/W1599364940","https://openalex.org/W1974627246","https://openalex.org/W2010416066","https://openalex.org/W2031248101","https://openalex.org/W2035720976","https://openalex.org/W2038276547","https://openalex.org/W2045263322","https://openalex.org/W2054141820","https://openalex.org/W2113741880","https://openalex.org/W2115854352","https://openalex.org/W2122090912","https://openalex.org/W2122146326","https://openalex.org/W2124509324","https://openalex.org/W2126754439","https://openalex.org/W2150886314","https://openalex.org/W2168356304","https://openalex.org/W2169054943","https://openalex.org/W2239648585","https://openalex.org/W2962863202","https://openalex.org/W2963056065","https://openalex.org/W2963593740","https://openalex.org/W2963703787","https://openalex.org/W3120740533","https://openalex.org/W4299379706","https://openalex.org/W6629956336","https://openalex.org/W6634599061","https://openalex.org/W6677671969","https://openalex.org/W6689953744"],"related_works":["https://openalex.org/W2429057255","https://openalex.org/W2187546663","https://openalex.org/W148745890","https://openalex.org/W4389670110","https://openalex.org/W2611942503","https://openalex.org/W4315621326","https://openalex.org/W2899790217","https://openalex.org/W2598865957","https://openalex.org/W2183040431","https://openalex.org/W2963557510"],"abstract_inverted_index":{"Recent":[0],"interest":[1],"in":[2,89],"the":[3,13,24,33,37,58,126,139,160,165,170,178,195,209,217,231],"problem":[4,26,38],"of":[5,15,27,35,62,74,96,141,183,188,202],"maximum":[6],"inner":[7],"product":[8],"search":[9,29],"(MIPS)":[10],"has":[11],"sparked":[12],"development":[14],"new":[16],"solutions.":[17],"The":[18,185,199],"solutions":[19,44,70],"(usually)":[20],"reduce":[21,151],"MIPS":[22,83,116,127,152,172],"to":[23,41,87,104,125,153,158,192,206],"well-studied":[25],"nearest-neighbour":[28],"(NNS).":[30],"To":[31,132],"escape":[32],"curse":[34],"dimensionality,":[36],"is":[39,50,57,94,117,129],"relaxed":[40],"accept":[42,47],"approximate":[43,59,120],"(that":[45],"is,":[46],"anything":[48],"that":[49,76],"approximately":[51],"maximum),":[52],"and":[53,92,113],"locality":[54],"sensitive":[55],"hashing":[56],"NNS":[60,88,154,161,167],"algorithm":[61],"choice.":[63],"While":[64],"being":[65],"extremely":[66],"resourceful,":[67],"these":[68,134],"existing":[69],"have":[71],"a":[72],"couple":[73],"aspects":[75],"can":[77,84],"be":[78,85],"improved":[79],"upon":[80],"-":[81],"(i)":[82],"reduced":[86],"multiple":[90],"ways":[91],"there":[93],"lack":[95],"understanding":[97],"(mostly":[98],"theoretical":[99,186],"but":[100,155],"also":[101],"empirical)":[102],"when":[103,115],"choose":[105,194],"which":[106],"reduction":[107],"for":[108,146,180],"best":[109,196],"accuracy":[110],"or":[111],"efficiency,":[112],"(ii)":[114],"solved":[118],"via":[119],"NNS,":[121],"translating":[122],"this":[123],"approximation":[124],"solution":[128,173],"not":[130],"straightforward.":[131],"overcome":[133],"usability":[135],"issues,":[136],"we":[137],"propose":[138],"use":[140],"randomized":[142],"partition":[143],"trees":[144],"(RPTs)":[145],"solving":[147],"MIPS.":[148],"We":[149],"still":[150],"utilize":[156],"RPTs":[157,163,189,203,225],"solve":[159],"problem.":[162],"find":[164],"exact":[166,171],"solution,":[168],"hence":[169],"(with":[174],"high":[175],"probability),":[176],"avoiding":[177],"need":[179],"any":[181],"translation":[182],"approximation.":[184],"properties":[187,201],"allow":[190,204],"us":[191,205],"definitively":[193],"MIPS-to-NNS":[197],"reduction.":[198],"empirical":[200],"significantly":[207],"outperform":[208],"state-of-the-art":[210],"while":[211],"providing":[212],"unique":[213],"fine-grained":[214],"control":[215],"over":[216],"accuracy-efficiency":[218],"tradeoff.":[219],"For":[220],"example,":[221],"at":[222],"80%":[223],"accuracy,":[224],"are":[226],"2-5\u00d7":[227],"more":[228],"efficient":[229],"than":[230],"state-of-the-art.":[232]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":3}],"updated_date":"2026-03-14T08:43:22.919905","created_date":"2025-10-10T00:00:00"}
