{"id":"https://openalex.org/W4388214012","doi":"https://doi.org/10.1109/jsait.2023.3328651","title":"Learning Invariant Representations Under General Interventions on the Response","display_name":"Learning Invariant Representations Under General Interventions on the Response","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4388214012","doi":"https://doi.org/10.1109/jsait.2023.3328651"},"language":"en","primary_location":{"id":"doi:10.1109/jsait.2023.3328651","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jsait.2023.3328651","pdf_url":null,"source":{"id":"https://openalex.org/S4210211895","display_name":"IEEE Journal on Selected Areas in Information Theory","issn_l":"2641-8770","issn":["2641-8770"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal on Selected Areas in Information Theory","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5087769384","display_name":"Kang Du","orcid":"https://orcid.org/0000-0002-6084-872X"},"institutions":[{"id":"https://openalex.org/I223532165","display_name":"University of Utah","ror":"https://ror.org/03r0ha626","country_code":"US","type":"education","lineage":["https://openalex.org/I223532165"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Kang Du","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Utah, Salt Lake City, UT, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Utah, Salt Lake City, UT, USA","institution_ids":["https://openalex.org/I223532165"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101595454","display_name":"Yu Xiang","orcid":"https://orcid.org/0000-0002-2891-9153"},"institutions":[{"id":"https://openalex.org/I223532165","display_name":"University of Utah","ror":"https://ror.org/03r0ha626","country_code":"US","type":"education","lineage":["https://openalex.org/I223532165"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yu Xiang","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Utah, Salt Lake City, UT, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Utah, Salt Lake City, UT, USA","institution_ids":["https://openalex.org/I223532165"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5087769384"],"corresponding_institution_ids":["https://openalex.org/I223532165"],"apc_list":null,"apc_paid":null,"fwci":1.0438,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.81793713,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"4","issue":null,"first_page":"808","last_page":"819"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9998000264167786,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9998000264167786,"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":0.9955000281333923,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.994700014591217,"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/invariant","display_name":"Invariant (physics)","score":0.5909754037857056},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5663447976112366},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5373002886772156},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5242640972137451},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5014455318450928},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43397608399391174},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.42513784766197205},{"id":"https://openalex.org/keywords/property","display_name":"Property (philosophy)","score":0.4109755754470825},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.3439905047416687},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.31211626529693604},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.12264692783355713}],"concepts":[{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.5909754037857056},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5663447976112366},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5373002886772156},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5242640972137451},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5014455318450928},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43397608399391174},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42513784766197205},{"id":"https://openalex.org/C189950617","wikidata":"https://www.wikidata.org/wiki/Q937228","display_name":"Property (philosophy)","level":2,"score":0.4109755754470825},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.3439905047416687},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.31211626529693604},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.12264692783355713},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C37914503","wikidata":"https://www.wikidata.org/wiki/Q156495","display_name":"Mathematical physics","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/jsait.2023.3328651","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jsait.2023.3328651","pdf_url":null,"source":{"id":"https://openalex.org/S4210211895","display_name":"IEEE Journal on Selected Areas in Information Theory","issn_l":"2641-8770","issn":["2641-8770"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal on Selected Areas in Information Theory","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":74,"referenced_works":["https://openalex.org/W1968018625","https://openalex.org/W1975846642","https://openalex.org/W2034180713","https://openalex.org/W2064447488","https://openalex.org/W2083211221","https://openalex.org/W2094607565","https://openalex.org/W2131953535","https://openalex.org/W2135046866","https://openalex.org/W2143891888","https://openalex.org/W2151226328","https://openalex.org/W2162651021","https://openalex.org/W2395579298","https://openalex.org/W2562747313","https://openalex.org/W2790376986","https://openalex.org/W2809895662","https://openalex.org/W2885305518","https://openalex.org/W2887788426","https://openalex.org/W2891587032","https://openalex.org/W2896457183","https://openalex.org/W2951040662","https://openalex.org/W2963062793","https://openalex.org/W2963608118","https://openalex.org/W2964317900","https://openalex.org/W2998115938","https://openalex.org/W3012148446","https://openalex.org/W3016824580","https://openalex.org/W3086992450","https://openalex.org/W3095575559","https://openalex.org/W3108961219","https://openalex.org/W3125774186","https://openalex.org/W3150893739","https://openalex.org/W3179971958","https://openalex.org/W3188960136","https://openalex.org/W3196915488","https://openalex.org/W3201584721","https://openalex.org/W3202150619","https://openalex.org/W4220917532","https://openalex.org/W4244473079","https://openalex.org/W4248181943","https://openalex.org/W4287825762","https://openalex.org/W4288287305","https://openalex.org/W4289306490","https://openalex.org/W4294016603","https://openalex.org/W4295150927","https://openalex.org/W4298090544","https://openalex.org/W4312537100","https://openalex.org/W4372341250","https://openalex.org/W4381059423","https://openalex.org/W4393395462","https://openalex.org/W6679908217","https://openalex.org/W6682361391","https://openalex.org/W6682658890","https://openalex.org/W6718795669","https://openalex.org/W6730877132","https://openalex.org/W6733525777","https://openalex.org/W6737943489","https://openalex.org/W6745454490","https://openalex.org/W6748353538","https://openalex.org/W6754046860","https://openalex.org/W6754646375","https://openalex.org/W6754817966","https://openalex.org/W6754927192","https://openalex.org/W6755174428","https://openalex.org/W6755207826","https://openalex.org/W6758595158","https://openalex.org/W6760602371","https://openalex.org/W6765285020","https://openalex.org/W6774861611","https://openalex.org/W6775444529","https://openalex.org/W6784247468","https://openalex.org/W6784537221","https://openalex.org/W6787668776","https://openalex.org/W6800550264","https://openalex.org/W6854513511"],"related_works":["https://openalex.org/W3162204513","https://openalex.org/W2371138613","https://openalex.org/W2048963458","https://openalex.org/W43109613","https://openalex.org/W2359952343","https://openalex.org/W2239445980","https://openalex.org/W2080152487","https://openalex.org/W3083152911","https://openalex.org/W2120455979","https://openalex.org/W2008149323"],"abstract_inverted_index":{"It":[0],"has":[1,21],"become":[2],"increasingly":[3],"common":[4],"nowadays":[5],"to":[6,22,26,33,40,46,96,102,132,140,188,202],"collect":[7],"observations":[8],"of":[9,62,100,144,151,168],"feature":[10],"and":[11,49,123,175],"response":[12,64,84,156],"pairs":[13],"from":[14],"different":[15,30],"environments.":[16,72,107],"As":[17],"a":[18,29,148,210],"consequence,":[19],"one":[20],"apply":[23],"learned":[24],"predictors":[25,67],"data":[27],"with":[28],"distribution":[31,34,61],"due":[32],"shifts.":[35],"One":[36],"principled":[37],"approach":[38],"is":[39,85,90,93,183],"adopt":[41],"the":[42,53,59,63,69,83,155,160,164,173,180,189],"structural":[43,119],"causal":[44,120],"models":[45,121],"describe":[47],"training":[48],"test":[50],"models,":[51],"following":[52],"invariance":[54,101,145],"principle":[55,75],"which":[56],"says":[57],"that":[58,146,197],"conditional":[60],"given":[65],"its":[66],"remains":[68],"same":[70],"across":[71],"However,":[73],"this":[74,112],"might":[76],"be":[77],"violated":[78],"in":[79,105],"practical":[80],"settings":[81,208],"when":[82],"intervened.":[86],"A":[87],"natural":[88],"question":[89],"whether":[91],"it":[92,187],"still":[94],"possible":[95],"identify":[97],"other":[98],"forms":[99],"facilitate":[103],"prediction":[104],"unseen":[106],"To":[108],"shed":[109],"light":[110],"on":[111,117,154],"challenging":[113],"scenario,":[114],"we":[115],"focus":[116],"linear":[118],"(SCMs)":[122],"introduce":[124],"invariant":[125],"matching":[126],"property":[127],"(IMP),":[128],"an":[129,136,141],"explicit":[130],"relation":[131],"capture":[133],"interventions":[134,153],"through":[135],"additional":[137],"feature,":[138],"leading":[139],"alternative":[142],"form":[143],"enables":[147],"unified":[149],"treatment":[150],"general":[152],"as":[157,159],"well":[158],"predictors.":[161],"We":[162,194],"analyze":[163],"asymptotic":[165],"generalization":[166],"errors":[167],"our":[169],"method":[170],"under":[171],"both":[172],"discrete":[174],"continuous":[176,181],"environment":[177],"settings,":[178],"where":[179],"case":[182],"handled":[184],"by":[185],"relating":[186],"semiparametric":[190],"varying":[191],"coefficient":[192],"models.":[193],"present":[195],"algorithms":[196],"show":[198],"competitive":[199],"performance":[200],"compared":[201],"existing":[203],"methods":[204],"over":[205],"various":[206],"experimental":[207],"including":[209],"COVID":[211],"dataset.":[212]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
