{"id":"https://openalex.org/W1971937213","doi":"https://doi.org/10.1109/isit.2014.6875352","title":"Compression for quadratic similarity queries via shape-gain quantizers","display_name":"Compression for quadratic similarity queries via shape-gain quantizers","publication_year":2014,"publication_date":"2014-06-01","ids":{"openalex":"https://openalex.org/W1971937213","doi":"https://doi.org/10.1109/isit.2014.6875352","mag":"1971937213"},"language":"en","primary_location":{"id":"doi:10.1109/isit.2014.6875352","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit.2014.6875352","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE International Symposium on Information Theory","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://mediatum.ub.tum.de/node?id=1303447","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5087174999","display_name":"Steffen Dempfle","orcid":null},"institutions":[{"id":"https://openalex.org/I62916508","display_name":"Technical University of Munich","ror":"https://ror.org/02kkvpp62","country_code":"DE","type":"education","lineage":["https://openalex.org/I62916508"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Steffen Dempfle","raw_affiliation_strings":["Technische Universit\u00e4t M\u00fcnchen, Munich, Germany","Tech. Univ. Munchen, Munich, Germany"],"affiliations":[{"raw_affiliation_string":"Technische Universit\u00e4t M\u00fcnchen, Munich, Germany","institution_ids":["https://openalex.org/I62916508"]},{"raw_affiliation_string":"Tech. Univ. Munchen, Munich, Germany","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027939859","display_name":"Fabian Steiner","orcid":"https://orcid.org/0000-0002-5162-2649"},"institutions":[{"id":"https://openalex.org/I62916508","display_name":"Technical University of Munich","ror":"https://ror.org/02kkvpp62","country_code":"DE","type":"education","lineage":["https://openalex.org/I62916508"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Fabian Steiner","raw_affiliation_strings":["Technische Universit\u00e4t M\u00fcnchen, Munich, Germany","Tech. Univ. Munchen, Munich, Germany"],"affiliations":[{"raw_affiliation_string":"Technische Universit\u00e4t M\u00fcnchen, Munich, Germany","institution_ids":["https://openalex.org/I62916508"]},{"raw_affiliation_string":"Tech. Univ. Munchen, Munich, Germany","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016461327","display_name":"Amir Ingber","orcid":"https://orcid.org/0000-0001-6639-8240"},"institutions":[{"id":"https://openalex.org/I4210134091","display_name":"Yahoo (United States)","ror":"https://ror.org/040dkzz12","country_code":"US","type":"company","lineage":["https://openalex.org/I4210134091"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Amir Ingber","raw_affiliation_strings":["Yahoo! Labs, Sunnyvale, CA","Yahoo! Labs., Sunnyvale, CA, USA"],"affiliations":[{"raw_affiliation_string":"Yahoo! Labs, Sunnyvale, CA","institution_ids":["https://openalex.org/I4210134091"]},{"raw_affiliation_string":"Yahoo! Labs., Sunnyvale, CA, USA","institution_ids":["https://openalex.org/I4210134091"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043344688","display_name":"Tsachy Weissman","orcid":"https://orcid.org/0009-0008-1099-691X"},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tsachy Weissman","raw_affiliation_strings":["Department of Electrical Engineering, Stanford University","[Dept. of Electr. Eng., Stanford Univ., Stanford, CA, USA]"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Stanford University","institution_ids":["https://openalex.org/I97018004"]},{"raw_affiliation_string":"[Dept. of Electr. Eng., Stanford Univ., Stanford, CA, USA]","institution_ids":["https://openalex.org/I97018004"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5087174999"],"corresponding_institution_ids":["https://openalex.org/I62916508"],"apc_list":null,"apc_paid":null,"fwci":0.2439,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.55275318,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"290","issue":null,"first_page":"2839","last_page":"2843"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10901","display_name":"Advanced Data Compression Techniques","score":0.9988999962806702,"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/T10901","display_name":"Advanced Data Compression Techniques","score":0.9988999962806702,"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":0.9986000061035156,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9901000261306763,"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/mathematics","display_name":"Mathematics","score":0.6608240008354187},{"id":"https://openalex.org/keywords/scalar","display_name":"Scalar (mathematics)","score":0.4953416883945465},{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.4896722137928009},{"id":"https://openalex.org/keywords/euclidean-distance","display_name":"Euclidean distance","score":0.47464093565940857},{"id":"https://openalex.org/keywords/upper-and-lower-bounds","display_name":"Upper and lower bounds","score":0.46766459941864014},{"id":"https://openalex.org/keywords/lattice","display_name":"Lattice (music)","score":0.44737353920936584},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4373071789741516},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4335162937641144},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.4234082102775574},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.30712056159973145},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.15731552243232727},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.10087904334068298}],"concepts":[{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.6608240008354187},{"id":"https://openalex.org/C57691317","wikidata":"https://www.wikidata.org/wiki/Q1289248","display_name":"Scalar (mathematics)","level":2,"score":0.4953416883945465},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.4896722137928009},{"id":"https://openalex.org/C120174047","wikidata":"https://www.wikidata.org/wiki/Q847073","display_name":"Euclidean distance","level":2,"score":0.47464093565940857},{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.46766459941864014},{"id":"https://openalex.org/C2781204021","wikidata":"https://www.wikidata.org/wiki/Q6497091","display_name":"Lattice (music)","level":2,"score":0.44737353920936584},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4373071789741516},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4335162937641144},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.4234082102775574},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.30712056159973145},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.15731552243232727},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.10087904334068298},{"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/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/isit.2014.6875352","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit.2014.6875352","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE International Symposium on Information Theory","raw_type":"proceedings-article"},{"id":"pmh:oai:mediatum.ub.tum.de:node/1303447","is_oa":true,"landing_page_url":"http://mediatum.ub.tum.de/node?id=1303447","pdf_url":null,"source":{"id":"https://openalex.org/S4306400453","display_name":"mediaTUM \u2013 the media and publications repository of the Technical University Munich (Technical University Munich)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I62916508","host_organization_name":"Technical University of Munich","host_organization_lineage":["https://openalex.org/I62916508"],"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":"","raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:mediatum.ub.tum.de:node/1303447","is_oa":true,"landing_page_url":"http://mediatum.ub.tum.de/node?id=1303447","pdf_url":null,"source":{"id":"https://openalex.org/S4306400453","display_name":"mediaTUM \u2013 the media and publications repository of the Technical University Munich (Technical University Munich)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I62916508","host_organization_name":"Technical University of Munich","host_organization_lineage":["https://openalex.org/I62916508"],"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":"","raw_type":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W87339831","https://openalex.org/W1495061042","https://openalex.org/W1634005169","https://openalex.org/W1950555890","https://openalex.org/W1984810686","https://openalex.org/W2098936473","https://openalex.org/W2130422479","https://openalex.org/W2150593711","https://openalex.org/W2164184339","https://openalex.org/W4246024215","https://openalex.org/W4292414116","https://openalex.org/W4294294113","https://openalex.org/W4299837225","https://openalex.org/W6629384756","https://openalex.org/W6640765386","https://openalex.org/W6646672099"],"related_works":["https://openalex.org/W3203142394","https://openalex.org/W2161474341","https://openalex.org/W4302615923","https://openalex.org/W1974101135","https://openalex.org/W2351061015","https://openalex.org/W2017509870","https://openalex.org/W4220731478","https://openalex.org/W2542937328","https://openalex.org/W4251141768","https://openalex.org/W4360952157"],"abstract_inverted_index":{"We":[0,61],"study":[1],"the":[2,11,21,29,34,37,42,58,77,85,90,108,114,137,156,168,172],"problem":[3,35],"of":[4,6,13,33,76,121,159,167,171],"compression":[5,39],"a":[7,49,64,96,118,123,148,153,165],"Gaussian":[8],"vector":[9,78],"for":[10,143],"purpose":[12],"similarity":[14,17],"identification,":[15],"where":[16],"is":[18,79,93],"defined":[19],"by":[20,113,131],"mean":[22],"square":[23],"Euclidean":[24],"distance":[25],"between":[26],"vectors.":[27],"While":[28],"asymptotical":[30],"fundamental":[31],"limits":[32],"-":[36,45],"minimal":[38],"rate":[40],"and":[41,84,104,133,135],"error":[43,115],"exponent":[44],"were":[46],"found":[47],"in":[48,52],"previous":[50],"work,":[51],"this":[53],"paper":[54],"we":[55,125,151],"focus":[56],"on":[57,70,89,155],"nonasymptotic":[59],"domain.":[60],"first":[62],"present":[63],"finite":[65],"blocklength":[66],"achievability":[67],"bound":[68,154],"based":[69],"shape-gain":[71],"quantization:":[72],"The":[73,99],"gain":[74],"(amplitude)":[75],"compressed":[80],"via":[81],"scalar":[82],"quantization,":[83],"shape":[86],"(the":[87],"projection":[88],"unit":[91],"sphere)":[92],"quantized":[94],"using":[95],"spherical":[97,128,162],"code.":[98],"results":[100],"are":[101],"numerically":[102],"evaluated,":[103],"they":[105],"converge":[106],"to":[107],"asymptotic":[109],"values":[110],"as":[111,140,164],"predicted":[112],"exponent.":[116],"For":[117],"practical":[119],"implementation":[120],"such":[122],"scheme,":[124],"use":[126,136],"wrapped":[127,161],"codes,":[129],"studied":[130],"Hamkins":[132],"Zeger,":[134],"Leech":[138],"lattice":[139],"an":[141,144],"example":[142],"underlying":[145,173],"lattice.":[146,174],"As":[147],"side":[149],"result,":[150],"obtain":[152],"covering":[157,169],"angle":[158],"any":[160],"code,":[163],"function":[166],"radius":[170]},"counts_by_year":[{"year":2016,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}