{"id":"https://openalex.org/W4396892922","doi":"https://doi.org/10.1145/3651613","title":"A faster FPRAS for #NFA","display_name":"A faster FPRAS for #NFA","publication_year":2024,"publication_date":"2024-05-10","ids":{"openalex":"https://openalex.org/W4396892922","doi":"https://doi.org/10.1145/3651613"},"language":"en","primary_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.1145/3651613","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3651613","source":{"id":"https://openalex.org/S4387289859","display_name":"Proceedings of the ACM on Management of Data","issn_l":"2836-6573","issn":["2836-6573"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true},"type":"article","type_crossref":"journal-article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3651613","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5041528950","display_name":"Kuldeep S. Meel","orcid":"https://orcid.org/0000-0001-9423-5270"},"institutions":[{"id":"https://openalex.org/I185261750","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087","country_code":"CA","type":"education","lineage":["https://openalex.org/I185261750"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Kuldeep S. Meel","raw_affiliation_strings":["University of Toronto, Toronto, ON, Canada"],"affiliations":[{"raw_affiliation_string":"University of Toronto, Toronto, ON, Canada","institution_ids":["https://openalex.org/I185261750"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101626747","display_name":"Sourav Chakraborty","orcid":"https://orcid.org/0000-0001-9518-6204"},"institutions":[{"id":"https://openalex.org/I6498739","display_name":"Indian Statistical Institute","ror":"https://ror.org/00q2w1j53","country_code":"IN","type":"education","lineage":["https://openalex.org/I6498739"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Sourav Chakraborty","raw_affiliation_strings":["Indian Statistical Institute, Kolkata, India"],"affiliations":[{"raw_affiliation_string":"Indian Statistical Institute, Kolkata, India","institution_ids":["https://openalex.org/I6498739"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016958234","display_name":"Umang Mathur","orcid":"https://orcid.org/0000-0002-7610-0660"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Umang Mathur","raw_affiliation_strings":["National University of Singapore, Singapore, Singapore"],"affiliations":[{"raw_affiliation_string":"National University of Singapore, Singapore, Singapore","institution_ids":["https://openalex.org/I165932596"]}]}],"institution_assertions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":0,"max":86},"biblio":{"volume":"2","issue":"2","first_page":"1","last_page":"22"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T12072","display_name":"Active Learning in Machine Learning Research","score":0.9989,"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/T12072","display_name":"Active Learning in Machine Learning Research","score":0.9989,"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/T11269","display_name":"Text Compression and Indexing Algorithms","score":0.9983,"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/T10601","display_name":"Handwriting Recognition and Text Detection","score":0.9983,"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/hashing","display_name":"Hashing","score":0.469759}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.39996406}],"mesh":[],"locations_count":1,"locations":[{"is_oa":true,"landing_page_url":"https://doi.org/10.1145/3651613","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3651613","source":{"id":"https://openalex.org/S4387289859","display_name":"Proceedings of the ACM on Management of Data","issn_l":"2836-6573","issn":["2836-6573"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.1145/3651613","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3651613","source":{"id":"https://openalex.org/S4387289859","display_name":"Proceedings of the ACM on Management of Data","issn_l":"2836-6573","issn":["2836-6573"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true},"sustainable_development_goals":[{"display_name":"Peace, justice, and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.71}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":11,"referenced_works":["https://openalex.org/W1631091010","https://openalex.org/W1972917397","https://openalex.org/W1988524530","https://openalex.org/W2546922927","https://openalex.org/W2668736619","https://openalex.org/W2948686875","https://openalex.org/W2979636764","https://openalex.org/W2997262806","https://openalex.org/W3210082818","https://openalex.org/W4252345548","https://openalex.org/W4379537637"],"related_works":["https://openalex.org/W4396701345","https://openalex.org/W4396696052","https://openalex.org/W4395014643","https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2382290278","https://openalex.org/W2376932109","https://openalex.org/W2358668433","https://openalex.org/W2001405890"],"abstract_inverted_index":{"Given":[0,128],"a":[1,11,98,105,120,158,164,242,365,430],"non-deterministic":[2],"finite":[3],"automaton":[4],"(NFA)":[5],"A":[6,220],"with":[7,104,311],"m":[8,340],"states,":[9],"and":[10,88,124,142,202,217,231,238,262,286,317,354,383,426],"natural":[12,159],"number":[13,252,297,376],"n":[14,34,111,316,337,342],"(presented":[15],"in":[16,51,90,134,152,155,189,197,212,223,333,406,423],"unary),":[17],"the":[18,24,27,39,45,54,63,95,129,139,144,172,175,190,224,246,251,269,289,296,369,372,375,394,397,437],"#NFA":[19,55,80,168,180,207],"problem":[20,42,56],"asks":[21],"to":[22,59,227,304,402,420],"determine":[23],"size":[25],"of":[26,30,32,43,47,97,108,136,138,147,178,214,236,253,259,271,284,298,371,374,377,396,411,440],"set":[28],"L(A,n)":[29,48],"words":[31],"length":[33,263,384],"accepted":[35],"by":[36,84],"A.":[37],"While":[38],"corresponding":[40],"decision":[41],"checking":[44],"emptiness":[46],"is":[49,57,70,162,209,234,400],"solvable":[50],"polynomial":[52,74,100],"time,":[53],"known":[58],"be":[60,305],"#P-hard.":[61],"Recently,":[62],"long-standing":[64],"open":[65,428],"question":[66,160,188],"---":[67,81,250],"whether":[68],"there":[69,163],"an":[71,204],"FPRAS":[72,166,205,225,290,331,353,363,390],"(fully":[73],"time":[75,106,132,198,216,334,424],"randomized":[76,101],"approximation":[77,102],"scheme)":[78],"for":[79,119,167,174,206,256,301,379,433,442],"was":[82],"resolved":[83],"Arenas,":[85,228],"Croquevielle,":[86,229],"Jayaram,":[87,230],"Riveros":[89,232],"[ACJR19].":[91],"The":[92,352],"authors":[93],"demonstrated":[94],"existence":[96],"fully":[99],"scheme":[103,270],"complexity":[107,133,199,425],"~O(m":[109],"17":[110,112],"\u2022":[113,116,345,348],"1/\u03b5":[114,346],"14":[115],"log":[117,349],"(1/\u03b4)),":[118],"given":[121],"tolerance":[122],"\u03b5":[123,278],"confidence":[125],"parameter":[126],"\u03b4.":[127],"prohibitively":[130],"high":[131],"terms":[135,213],"each":[137,257,302,380],"input":[140],"parameters,":[141],"considering":[143],"widespread":[145],"application":[146],"approximate":[148,179,443],"counting":[149],"(and":[150],"sampling)":[151],"various":[153],"tasks":[154],"Computer":[156],"Science,":[157],"arises:":[161],"faster":[165],"that":[169,194,208,393],"can":[170],"pave":[171],"way":[173],"practical":[176,438],"implementation":[177,439],"tools?":[181],"In":[182,267,288],"this":[183,187],"work,":[184],"we":[185,291,293],"answer":[186],"positive.":[191],"We":[192,414],"demonstrate":[193],"significant":[195],"improvements":[196],"are":[200],"achievable,":[201],"propose":[203],"more":[210,247],"efficient":[211],"both":[215],"sample":[218],"complexity.":[219],"key":[221],"ingredient":[222],"due":[226],"[ACJR19]":[233,272],"inter-reducibility":[235],"sampling":[237],"counting,":[239],"which":[240],"necessitates":[241],"closer":[243],"look":[244],"at":[245],"informative":[248],"measure":[249],"samples":[254,281,299,326,378,398],"maintained":[255,399],"pair":[258,283],"state":[260,285,303,381],"q":[261,382],"i":[264,385],"<=":[265,386],"n.":[266,387],"particular,":[268],"maintains":[273,364],"O(m":[274],"7":[275,277,279],"/n":[276],")":[280,325,344],"per":[282,327],"length.":[287],"propose,":[292],"systematically":[294],"reduce":[295],"required":[300],"only":[306,320,391,405],"poly-logarithmically":[307],"dependent":[308],"on":[309,315],"m,":[310],"significantly":[312],"less":[313],"dependence":[314],"\u03b5,":[318],"maintaining":[319],"~O(n":[321],"4":[322,347],"/\u03b5":[323],"2":[324,336,350],"state.":[328],"Consequently,":[329],"our":[330,362,389,416],"runs":[332],"~O((m":[335],"10":[338],"+":[339],"3":[341],"6":[343],"(1/\u03b4)).":[351],"its":[355],"analysis":[356],"use":[357],"several":[358],"novel":[359],"insights.":[360],"First,":[361],"weaker":[366],"invariant":[367],"about":[368],"quality":[370],"estimate":[373],"Second,":[388],"requires":[392],"distribution":[395,404],"close":[401],"uniform":[403],"total":[407],"variation":[408],"distance":[409],"(instead":[410],"maximum":[412],"norm).":[413],"believe":[415],"insights":[417],"may":[418],"lead":[419],"further":[421],"reductions":[422],"thus":[427],"up":[429],"promising":[431],"avenue":[432],"future":[434],"work":[435],"towards":[436],"tools":[441],"#NFA.":[444]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4396892922","counts_by_year":[],"updated_date":"2024-10-23T13:59:59.689859","created_date":"2024-05-15"}