{"id":"https://openalex.org/W3177464691","doi":"https://doi.org/10.1145/3448016.3457332","title":"Shahin: Faster Algorithms for Generating Explanations for Multiple Predictions","display_name":"Shahin: Faster Algorithms for Generating Explanations for Multiple Predictions","publication_year":2021,"publication_date":"2021-06-09","ids":{"openalex":"https://openalex.org/W3177464691","doi":"https://doi.org/10.1145/3448016.3457332","mag":"3177464691"},"language":"en","primary_location":{"id":"doi:10.1145/3448016.3457332","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3448016.3457332","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3448016.3457332","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2021 International Conference on Management of Data","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/10.1145/3448016.3457332","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5038301042","display_name":"Sona Hasani","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":true,"raw_author_name":"Sona Hasani","raw_affiliation_strings":["Google, San Francisco, CA, USA"],"affiliations":[{"raw_affiliation_string":"Google, San Francisco, CA, USA","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066004392","display_name":"Saravanan Thirumuruganathan","orcid":"https://orcid.org/0000-0002-1517-480X"},"institutions":[{"id":"https://openalex.org/I4210144839","display_name":"Hamad bin Khalifa University","ror":"https://ror.org/03eyq4y97","country_code":"QA","type":"education","lineage":["https://openalex.org/I4210144839"]}],"countries":["QA"],"is_corresponding":false,"raw_author_name":"Saravanan Thirumuruganathan","raw_affiliation_strings":["QCRI, Hamad Bin Khalifa University, Doha, Qatar"],"affiliations":[{"raw_affiliation_string":"QCRI, Hamad Bin Khalifa University, Doha, Qatar","institution_ids":["https://openalex.org/I4210144839"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035257754","display_name":"Nick Koudas","orcid":"https://orcid.org/0000-0001-5648-0638"},"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":"Nick Koudas","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":"last","author":{"id":"https://openalex.org/A5002203026","display_name":"Gautam Das","orcid":"https://orcid.org/0000-0002-4627-9065"},"institutions":[{"id":"https://openalex.org/I189196454","display_name":"The University of Texas at Arlington","ror":"https://ror.org/019kgqr73","country_code":"US","type":"education","lineage":["https://openalex.org/I189196454"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gautam Das","raw_affiliation_strings":["University of Texas Arlington, Arlington, TX, USA"],"affiliations":[{"raw_affiliation_string":"University of Texas Arlington, Arlington, TX, USA","institution_ids":["https://openalex.org/I189196454"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5038301042"],"corresponding_institution_ids":["https://openalex.org/I1291425158"],"apc_list":null,"apc_paid":null,"fwci":0.136,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.53332754,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"2235","last_page":"2243"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9997000098228455,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9997000098228455,"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/T11986","display_name":"Scientific Computing and Data Management","score":0.9925000071525574,"subfield":{"id":"https://openalex.org/subfields/1802","display_name":"Information Systems and Management"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9916999936103821,"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":0.8051338195800781},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.7610397338867188},{"id":"https://openalex.org/keywords/heuristics","display_name":"Heuristics","score":0.7571026086807251},{"id":"https://openalex.org/keywords/speedup","display_name":"Speedup","score":0.6913180947303772},{"id":"https://openalex.org/keywords/implementation","display_name":"Implementation","score":0.6128338575363159},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5291669368743896},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5223551988601685},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5020742416381836},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.4418611526489258},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.43470197916030884},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3664376139640808},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.29992151260375977},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.09596198797225952}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8051338195800781},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7610397338867188},{"id":"https://openalex.org/C127705205","wikidata":"https://www.wikidata.org/wiki/Q5748245","display_name":"Heuristics","level":2,"score":0.7571026086807251},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.6913180947303772},{"id":"https://openalex.org/C26713055","wikidata":"https://www.wikidata.org/wiki/Q245962","display_name":"Implementation","level":2,"score":0.6128338575363159},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5291669368743896},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5223551988601685},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5020742416381836},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.4418611526489258},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.43470197916030884},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3664376139640808},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.29992151260375977},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.09596198797225952},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3448016.3457332","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3448016.3457332","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3448016.3457332","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2021 International Conference on Management of Data","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3448016.3457332","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3448016.3457332","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3448016.3457332","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2021 International Conference on Management of Data","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1746585810","display_name":null,"funder_award_id":"2008602, 1745925, 1937143 and 2037433","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3177464691.pdf","grobid_xml":"https://content.openalex.org/works/W3177464691.grobid-xml"},"referenced_works_count":30,"referenced_works":["https://openalex.org/W2058978608","https://openalex.org/W2098416578","https://openalex.org/W2129888542","https://openalex.org/W2282821441","https://openalex.org/W2493343568","https://openalex.org/W2598262646","https://openalex.org/W2618851150","https://openalex.org/W2752236330","https://openalex.org/W2788403449","https://openalex.org/W2884753653","https://openalex.org/W2891503716","https://openalex.org/W2901939789","https://openalex.org/W2911280950","https://openalex.org/W2946123203","https://openalex.org/W2948252829","https://openalex.org/W2951660660","https://openalex.org/W2963847595","https://openalex.org/W2970102549","https://openalex.org/W3030350595","https://openalex.org/W3045317501","https://openalex.org/W3098054859","https://openalex.org/W3120740533","https://openalex.org/W3138819813","https://openalex.org/W4245107420","https://openalex.org/W4288414189","https://openalex.org/W4402843978","https://openalex.org/W6748883668","https://openalex.org/W6775951366","https://openalex.org/W6790587931","https://openalex.org/W6814897140"],"related_works":["https://openalex.org/W2058965144","https://openalex.org/W2164382479","https://openalex.org/W98480971","https://openalex.org/W2150291671","https://openalex.org/W2027972911","https://openalex.org/W2146343568","https://openalex.org/W2013643406","https://openalex.org/W2157978810","https://openalex.org/W1500978221","https://openalex.org/W1966837078"],"abstract_inverted_index":{"Machine":[0],"learning":[1],"(ML)":[2],"models":[3],"have":[4,46],"achieved":[5],"widespread":[6],"adoption":[7],"in":[8,50,88,104,189],"the":[9,25,29,60,176],"last":[10],"few":[11],"years.":[12],"Generating":[13],"concise":[14],"and":[15,22,112,119,133,158,171],"accurate":[16],"explanations":[17,44,73,87,188],"often":[18,45],"increases":[19],"user":[20],"trust":[21],"understanding":[23],"of":[24,31,62,141,153],"model":[26],"prediction.":[27,41,78],"Usually,":[28],"implementations":[30],"popular":[32],"explanation":[33,127,144,177],"algorithms":[34,154],"are":[35,102,131],"highly":[36],"optimized":[37],"for":[38,53,70,74,115,123],"a":[39,51,57,105,110,138,150,190],"single":[40],"In":[42],"practice,":[43],"to":[47,85,137,175],"be":[48,135],"generated":[49],"batch":[52,106],"multiple":[54,83],"predictions":[55],"at":[56],"time.":[58],"To":[59],"best":[61],"our":[63,165],"knowledge,":[64],"there":[65],"has":[66],"been":[67],"no":[68],"work":[69],"efficiently":[71],"generating":[72],"more":[75],"than":[76],"one":[77,80],"While":[79],"could":[81,134],"use":[82],"machines":[84],"generate":[86,187],"parallel,":[89],"this":[90,148],"approach":[91,114],"is":[92],"sub-optimal":[93],"as":[94],"it":[95],"does":[96],"not":[97],"leverage":[98],"higher-level":[99],"optimizations":[100],"that":[101,164,186],"available":[103],"setting.":[107],"We":[108,146],"propose":[109],"principled":[111],"lightweight":[113],"identifying":[116],"redundant":[117],"computations":[118],"several":[120],"effective":[121],"heuristics":[122],"dramatically":[124],"speeding":[125],"up":[126],"generation.":[128],"Our":[129,160],"techniques":[130],"general":[132],"applied":[136],"wide":[139],"variety":[140],"perturbation":[142],"based":[143],"algorithms.":[145,178],"demonstrate":[147],"over":[149,183],"diverse":[151],"set":[152],"including,":[155],"LIME,":[156],"Anchor,":[157],"SHAP.":[159],"empirical":[161],"experiments":[162],"show":[163],"methods":[166],"impose":[167],"very":[168],"little":[169],"overhead":[170],"require":[172],"minimal":[173],"modification":[174],"They":[179],"achieve":[180],"significant":[181],"speedup":[182],"baseline":[184],"approaches":[185],"sequential":[191],"manner.":[192]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
