{"id":"https://openalex.org/W2056506909","doi":"https://doi.org/10.1145/2806416.2806421","title":"An Optimal Online Algorithm For Retrieving Heavily Perturbed Statistical Databases In The Low-Dimensional Querying Model","display_name":"An Optimal Online Algorithm For Retrieving Heavily Perturbed Statistical Databases In The Low-Dimensional Querying Model","publication_year":2015,"publication_date":"2015-10-17","ids":{"openalex":"https://openalex.org/W2056506909","doi":"https://doi.org/10.1145/2806416.2806421","mag":"2056506909"},"language":"en","primary_location":{"id":"doi:10.1145/2806416.2806421","is_oa":true,"landing_page_url":"https://doi.org/10.1145/2806416.2806421","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/2806416.2806421","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 24th ACM International on Conference on Information and Knowledge Management","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/2806416.2806421","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5031842812","display_name":"Krzysztof Choroma\u0144ski","orcid":"https://orcid.org/0000-0003-3626-414X"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Krzysztof Marcin Choromanski","raw_affiliation_strings":["Google, New York, NY, USA"],"affiliations":[{"raw_affiliation_string":"Google, New York, NY, USA","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089765894","display_name":"Afshin Rostamizadeh","orcid":null},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Afshin Rostamizadeh","raw_affiliation_strings":["Google, New York, NY, USA"],"affiliations":[{"raw_affiliation_string":"Google, New York, NY, USA","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103121691","display_name":"Umar Syed","orcid":"https://orcid.org/0009-0007-3797-3614"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Umar Syed","raw_affiliation_strings":["Google, New York, NY, Tuvalu","Google, New York, NY, Tuvalu#TAB#"],"affiliations":[{"raw_affiliation_string":"Google, New York, NY, Tuvalu","institution_ids":["https://openalex.org/I1291425158"]},{"raw_affiliation_string":"Google, New York, NY, Tuvalu#TAB#","institution_ids":["https://openalex.org/I1291425158"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5031842812"],"corresponding_institution_ids":["https://openalex.org/I1291425158"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.04545358,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1381","last_page":"1390"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9991000294685364,"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"}},"topics":[{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9991000294685364,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.998199999332428,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9968000054359436,"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":0.6884720921516418},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.6451319456100464},{"id":"https://openalex.org/keywords/oracle","display_name":"Oracle","score":0.5867674946784973},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5734675526618958},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.5625271797180176},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.49000468850135803},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.43091264367103577},{"id":"https://openalex.org/keywords/online-algorithm","display_name":"Online algorithm","score":0.4211556315422058},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.4112771153450012},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3449617624282837},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2381109893321991},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.21042808890342712}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6884720921516418},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6451319456100464},{"id":"https://openalex.org/C55166926","wikidata":"https://www.wikidata.org/wiki/Q2892946","display_name":"Oracle","level":2,"score":0.5867674946784973},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5734675526618958},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.5625271797180176},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.49000468850135803},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.43091264367103577},{"id":"https://openalex.org/C196921405","wikidata":"https://www.wikidata.org/wiki/Q786431","display_name":"Online algorithm","level":2,"score":0.4211556315422058},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.4112771153450012},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3449617624282837},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2381109893321991},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.21042808890342712},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2806416.2806421","is_oa":true,"landing_page_url":"https://doi.org/10.1145/2806416.2806421","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/2806416.2806421","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 24th ACM International on Conference on Information and Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/2806416.2806421","is_oa":true,"landing_page_url":"https://doi.org/10.1145/2806416.2806421","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/2806416.2806421","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 24th ACM International on Conference on Information and Knowledge Management","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.5199999809265137,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2056506909.pdf","grobid_xml":"https://content.openalex.org/works/W2056506909.grobid-xml"},"referenced_works_count":21,"referenced_works":["https://openalex.org/W1502953220","https://openalex.org/W1986070285","https://openalex.org/W2009611335","https://openalex.org/W2031633693","https://openalex.org/W2047656932","https://openalex.org/W2061375390","https://openalex.org/W2093089717","https://openalex.org/W2097308346","https://openalex.org/W2110868467","https://openalex.org/W2118123209","https://openalex.org/W2120806354","https://openalex.org/W2124765629","https://openalex.org/W2196697156","https://openalex.org/W2285181575","https://openalex.org/W2293768274","https://openalex.org/W2799087070","https://openalex.org/W2911978475","https://openalex.org/W2952313324","https://openalex.org/W6630051280","https://openalex.org/W6750481014","https://openalex.org/W6824583106"],"related_works":["https://openalex.org/W2073713056","https://openalex.org/W3110702597","https://openalex.org/W4296209631","https://openalex.org/W2125620709","https://openalex.org/W2110441383","https://openalex.org/W1498872724","https://openalex.org/W4233149903","https://openalex.org/W2524540579","https://openalex.org/W2326878701","https://openalex.org/W4293864700"],"abstract_inverted_index":{"We":[0,81,184],"give":[1],"the":[2,18,31,37,67,83,89,106,109,113,126,130,133,137,148,168,182,204,233,255,258,267,280,283,292],"first":[3],"\u00d5(1":[4,220],"over":[5,221],"\u221a":[6],"T)-error":[7],"online":[8,74],"algorithm":[9,26,97,127,138,151,215,261],"for":[10,189],"reconstructing":[11],"noisy":[12],"statistical":[13],"databases,":[14],"where":[15,103],"T":[16,212],"is":[17,27,86,105,117,123,173,179],"number":[19],"of":[20,36,64,91,108,167,194,211,250,282,294],"(online)":[21],"sample":[22],"queries":[23,65,213],"received.":[24],"The":[25,95,150],"optimal":[28],"up":[29],"to":[30,47,59,112,128,146,155,196,232,272],"poly(log(T))":[32],"factor":[33],"in":[34,54,57,72,99,266,291],"terms":[35],"error":[38,219],"and":[39,290],"requires":[40],"only":[41,152,287],"O(log":[42],"T)":[43],"memory.":[44],"It":[45],"aims":[46],"learn":[48,129,147],"a":[49,62,92,156,163,176,190,209,242,248,251],"hidden":[50,68],"database-vector":[51,169,252],"w*":[52,253],"\u0395":[53],"\u211c":[55],"D":[56,85],"order":[58],"accurately":[60],"answer":[61],"stream":[63,134,210],"regarding":[66],"database,":[69],"which":[70,136,178],"arrive":[71],"an":[73,217],"fashion":[75],"from":[76],"some":[77],"unknown":[78],"distribution":[79,84],"D.":[80],"assume":[82],"defined":[87],"on":[88,135,203,236],"neighborhood":[90],"low-dimensional":[93],"manifold.":[94],"presented":[96],"runs":[98],"O(dD)-time":[100],"per":[101],"query,":[102],"d":[104],"dimensionality":[107],"query-space.":[110,259],"Contrary":[111],"classical":[114],"setting,":[115],"there":[116],"no":[118],"separate":[119],"training":[120],"set":[121],"that":[122,160,186,285],"used":[124,145],"by":[125,181,223,277],"database":[131],"---":[132],"will":[139],"be":[140,144,197,263],"evaluated":[141],"must":[142],"also":[143,264],"database-vector.":[149],"has":[153],"access":[154],"binary":[157,288],"oracle":[158,234],"\u039f":[159],"answers":[161,239],"whether":[162],"particular":[164],"linear":[165],"function":[166],"plus":[170],"random":[171,226],"noise":[172,195,206],"larger":[174],"than":[175],"threshold,":[177],"specified":[180],"algorithm.":[183],"note":[185],"we":[187],"allow":[188],"significant":[191,295],"O(D)":[192],"amount":[193],"added":[198],"while":[199],"other":[200],"works":[201],"focused":[202],"low":[205],"o(\u221aD)-setting.":[207],"For":[208],"our":[214],"achieves":[216],"average":[218],"\u221aT)":[222],"filtering":[224],"out":[225],"noise,":[227],"adapting":[228],"threshold":[229],"values":[230],"given":[231],"based":[235],"its":[237],"previous":[238],"and,":[240],"as":[241],"consequence,":[243],"recovering":[244],"with":[245],"high":[246],"precision":[247],"projection":[249],"onto":[254],"manifold":[256],"defining":[257],"Our":[260],"may":[262],"applied":[265],"adversarial":[268],"machine":[269,274],"learning":[270,275],"context":[271],"compromise":[273],"engines":[276],"heavily":[278],"exploiting":[279],"vulnerabilities":[281],"systems":[284],"output":[286],"signal":[289],"presence":[293],"noise.":[296]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
