{"id":"https://openalex.org/W3110200765","doi":"https://doi.org/10.48550/arxiv.2012.01536","title":"Improving KernelSHAP: Practical Shapley Value Estimation via Linear Regression","display_name":"Improving KernelSHAP: Practical Shapley Value Estimation via Linear Regression","publication_year":2020,"publication_date":"2020-12-02","ids":{"openalex":"https://openalex.org/W3110200765","doi":"https://doi.org/10.48550/arxiv.2012.01536","mag":"3110200765"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2012.01536","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2012.01536","pdf_url":"https://arxiv.org/pdf/2012.01536","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"text"},"volume":null,"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2012.01536","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5049580723","display_name":"Ian Covert","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Covert, Ian","raw_affiliation_strings":["University of Washington University of Washington"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Washington University of Washington","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5028723221","display_name":"Su\u2010In Lee","orcid":"https://orcid.org/0000-0001-5833-5215","observed_orcids":["https://orcid.org/0000-0001-5833-5215"]},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lee, Su-In","raw_affiliation_strings":["University of Washington University of Washington"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Washington University of Washington","institution_ids":["https://openalex.org/I201448701"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I201448701"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":24,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":1.0,"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":1.0,"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/T10743","display_name":"Software Testing and Debugging Techniques","score":0.0,"subfield":{"id":"https://openalex.org/subfields/1712","display_name":"Software"},"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.0,"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/kernelshap","display_name":"KernelSHAP","score":0.9440000057220459},{"id":"https://openalex.org/keywords/shapley-value","display_name":"Shapley value","score":0.8809999823570251},{"id":"https://openalex.org/keywords/explainable-ai","display_name":"explainable AI","score":0.6710000038146973},{"id":"https://openalex.org/keywords/model-agnostic-explanation","display_name":"model-agnostic explanation","score":0.7020000219345093},{"id":"https://openalex.org/keywords/linear-regression-estimation","display_name":"linear regression estimation","score":0.7459999918937683},{"id":"https://openalex.org/keywords/convergence-detection","display_name":"convergence detection","score":0.7889999747276306},{"id":"https://openalex.org/keywords/uncertainty-estimation","display_name":"uncertainty estimation","score":0.9850000143051147},{"id":"https://openalex.org/keywords/variance-reduction","display_name":"variance reduction","score":0.9430000185966492},{"id":"https://openalex.org/keywords/model-interpretability","display_name":"model interpretability","score":0.4650000035762787}],"concepts":[{"id":"https://openalex.org/C199022921","wikidata":"https://www.wikidata.org/wiki/Q240046","display_name":"Shapley value","level":3,"score":0.8267347812652588},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.8192142248153687},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.6976175308227539},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.6384899616241455},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.49615082144737244},{"id":"https://openalex.org/C2776291640","wikidata":"https://www.wikidata.org/wiki/Q2912517","display_name":"Value (mathematics)","level":2,"score":0.46283650398254395},{"id":"https://openalex.org/C62644790","wikidata":"https://www.wikidata.org/wiki/Q3454689","display_name":"Variance reduction","level":3,"score":0.41372209787368774},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.399058073759079},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3819408416748047},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.3565590977668762},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.35638585686683655},{"id":"https://openalex.org/C177142836","wikidata":"https://www.wikidata.org/wiki/Q44455","display_name":"Game theory","level":2,"score":0.26826637983322144},{"id":"https://openalex.org/C144237770","wikidata":"https://www.wikidata.org/wiki/Q747534","display_name":"Mathematical economics","level":1,"score":0.21740907430648804},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1796894669532776},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.12040668725967407},{"id":"https://openalex.org/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","level":1,"score":0.0},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"pmh:oai:arXiv.org:2012.01536","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2012.01536","pdf_url":"https://arxiv.org/pdf/2012.01536","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"text"},{"id":"mag:3110200765","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/pdf/2012.01536.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.2012.01536","doi":"https://doi.org/10.48550/arxiv.2012.01536","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2012.01536","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2012.01536","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2012.01536","pdf_url":"https://arxiv.org/pdf/2012.01536","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G1204744554","display_name":"CAREER: Learning the Chromatin Network from ChIP-Seq Data","funder_award_id":"1552309","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G3840858288","display_name":"Collaborative Research: ABI Innovation: Interpretable Machine Learning to Identify Molecular Markers for Complex Phenotypes","funder_award_id":"1759487","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"},{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"},{"id":"https://openalex.org/F4320337337","display_name":"National Institute on Aging","ror":"https://ror.org/049v75w11"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3110200765.pdf","grobid_xml":"https://content.openalex.org/works/W3110200765.grobid-xml"},"referenced_works_count":41,"referenced_works":["https://openalex.org/W103945154","https://openalex.org/W1562353621","https://openalex.org/W1966062834","https://openalex.org/W1971916086","https://openalex.org/W1987034518","https://openalex.org/W2021873163","https://openalex.org/W2073231946","https://openalex.org/W2075784261","https://openalex.org/W2085268307","https://openalex.org/W2091836314","https://openalex.org/W2110301906","https://openalex.org/W2125298525","https://openalex.org/W2129888542","https://openalex.org/W2130486630","https://openalex.org/W2135046866","https://openalex.org/W2149426898","https://openalex.org/W2203370306","https://openalex.org/W2276615843","https://openalex.org/W2282821441","https://openalex.org/W2296319761","https://openalex.org/W2335900909","https://openalex.org/W2510508396","https://openalex.org/W2518039540","https://openalex.org/W2618851150","https://openalex.org/W2768348081","https://openalex.org/W2795441251","https://openalex.org/W2887533108","https://openalex.org/W2924181074","https://openalex.org/W2939984132","https://openalex.org/W2964022491","https://openalex.org/W2999615587","https://openalex.org/W3007233875","https://openalex.org/W3014290757","https://openalex.org/W3035561175","https://openalex.org/W3038107861","https://openalex.org/W3080898047","https://openalex.org/W3087682678","https://openalex.org/W3094321430","https://openalex.org/W3107600318","https://openalex.org/W3120740533","https://openalex.org/W3122480604"],"related_works":["https://openalex.org/W3157402184","https://openalex.org/W4416528619","https://openalex.org/W4403853934","https://openalex.org/W4416380181","https://openalex.org/W4415069566","https://openalex.org/W4393306796","https://openalex.org/W3179224442","https://openalex.org/W7160848535","https://openalex.org/W3094179526","https://openalex.org/W7127313621"],"abstract_inverted_index":{"The":[0],"Shapley":[1,36],"value":[2],"concept":[3],"from":[4],"cooperative":[5,113],"game":[6],"theory":[7],"has":[8],"become":[9],"a":[10,54,78,92,107],"popular":[11],"technique":[12,95],"for":[13,85,111,120],"interpreting":[14],"ML":[15],"models,":[16],"but":[17],"efficiently":[18],"estimating":[19,35],"these":[20],"values":[21,37],"remains":[22],"challenging,":[23],"particularly":[24],"in":[25,81,83],"the":[26,32,50,74,99],"model-agnostic":[27],"setting.":[28],"Here,":[29],"we":[30,59,90,105],"revisit":[31],"idea":[33],"of":[34,101,109],"via":[38],"linear":[39],"regression":[40],"to":[41,62],"understand":[42],"and":[43,66,89],"improve":[44],"upon":[45],"this":[46],"approach.":[47],"By":[48],"analyzing":[49],"original":[51,75],"KernelSHAP":[52,110],"alongside":[53],"newly":[55],"proposed":[56],"unbiased":[57],"version,":[58],"develop":[60,106],"techniques":[61],"detect":[63],"its":[64],"convergence":[65,100],"calculate":[67],"uncertainty":[68],"estimates.":[69],"We":[70],"also":[71],"find":[72],"that":[73,96,115],"version":[76,108],"incurs":[77],"negligible":[79],"increase":[80],"bias":[82],"exchange":[84],"significantly":[86],"lower":[87],"variance,":[88],"propose":[91],"variance":[93],"reduction":[94],"further":[97],"accelerates":[98],"both":[102],"estimators.":[103],"Finally,":[104],"stochastic":[112],"games":[114],"yields":[116],"fast":[117],"new":[118],"estimators":[119],"two":[121],"global":[122],"explanation":[123],"methods.":[124]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3}],"updated_date":"2026-11-05T12:25:35.769452","created_date":"2020-12-07T00:00:00"}
