{"id":"https://openalex.org/W4367300158","doi":"https://doi.org/10.3390/a16050226","title":"Heterogeneous Treatment Effect with Trained Kernels of the Nadaraya\u2013Watson Regression","display_name":"Heterogeneous Treatment Effect with Trained Kernels of the Nadaraya\u2013Watson Regression","publication_year":2023,"publication_date":"2023-04-27","ids":{"openalex":"https://openalex.org/W4367300158","doi":"https://doi.org/10.3390/a16050226"},"language":"en","primary_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.3390/a16050226","pdf_url":"https://www.mdpi.com/1999-4893/16/5/226/pdf?version=1682590965","source":{"id":"https://openalex.org/S190629608","display_name":"Algorithms","issn_l":"1999-4893","issn":["1999-4893"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"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":"gold","oa_url":"https://www.mdpi.com/1999-4893/16/5/226/pdf?version=1682590965","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5062600336","display_name":"Andrei V. Konstantinov","orcid":"https://orcid.org/0000-0002-1542-6480"},"institutions":[{"id":"https://openalex.org/I212220629","display_name":"Peter the Great St. Petersburg Polytechnic University","ror":"https://ror.org/02x91aj62","country_code":"RU","type":"education","lineage":["https://openalex.org/I212220629"]}],"countries":["RU"],"is_corresponding":false,"raw_author_name":"Andrei Konstantinov","raw_affiliation_strings":["Institute of Computer Science and Technology, Peter the Great St. Petersburg Polytechnic University, Polytechnicheskaya, 29, 195251 St. Petersburg, Russia"],"affiliations":[{"raw_affiliation_string":"Institute of Computer Science and Technology, Peter the Great St. Petersburg Polytechnic University, Polytechnicheskaya, 29, 195251 St. Petersburg, Russia","institution_ids":["https://openalex.org/I212220629"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050293875","display_name":"Stanislav R. Kirpichenko","orcid":"https://orcid.org/0000-0003-2275-1473"},"institutions":[{"id":"https://openalex.org/I212220629","display_name":"Peter the Great St. Petersburg Polytechnic University","ror":"https://ror.org/02x91aj62","country_code":"RU","type":"education","lineage":["https://openalex.org/I212220629"]}],"countries":["RU"],"is_corresponding":false,"raw_author_name":"Stanislav Kirpichenko","raw_affiliation_strings":["Institute of Computer Science and Technology, Peter the Great St. Petersburg Polytechnic University, Polytechnicheskaya, 29, 195251 St. Petersburg, Russia"],"affiliations":[{"raw_affiliation_string":"Institute of Computer Science and Technology, Peter the Great St. Petersburg Polytechnic University, Polytechnicheskaya, 29, 195251 St. Petersburg, Russia","institution_ids":["https://openalex.org/I212220629"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037096829","display_name":"Lev V. Utkin","orcid":"https://orcid.org/0000-0002-5637-1420"},"institutions":[{"id":"https://openalex.org/I212220629","display_name":"Peter the Great St. Petersburg Polytechnic University","ror":"https://ror.org/02x91aj62","country_code":"RU","type":"education","lineage":["https://openalex.org/I212220629"]}],"countries":["RU"],"is_corresponding":true,"raw_author_name":"Lev Utkin","raw_affiliation_strings":["Institute of Computer Science and Technology, Peter the Great St. Petersburg Polytechnic University, Polytechnicheskaya, 29, 195251 St. Petersburg, Russia"],"affiliations":[{"raw_affiliation_string":"Institute of Computer Science and Technology, Peter the Great St. Petersburg Polytechnic University, Polytechnicheskaya, 29, 195251 St. Petersburg, Russia","institution_ids":["https://openalex.org/I212220629"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5037096829"],"corresponding_institution_ids":["https://openalex.org/I212220629"],"apc_list":{"value":1400,"currency":"CHF","value_usd":1515,"provenance":"doaj"},"apc_paid":{"value":1400,"currency":"CHF","value_usd":1515,"provenance":"doaj"},"fwci":0.53,"has_fulltext":true,"fulltext_origin":"pdf","cited_by_count":1,"citation_normalized_percentile":{"value":0.590864,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":68,"max":79},"biblio":{"volume":"16","issue":"5","first_page":"226","last_page":"226"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9994,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9994,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10845","display_name":"Advanced Causal Inference Techniques","score":0.9993,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.9806,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/watson","display_name":"Watson","score":0.705704},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.6048104},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4386746}],"concepts":[{"id":"https://openalex.org/C2776608531","wikidata":"https://www.wikidata.org/wiki/Q12253","display_name":"Watson","level":2,"score":0.705704},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.65302944},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.6048104},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.58427906},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5190252},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.48407307},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46841636},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.463237},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4386746},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36317897},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3186073},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.26196396},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.088597804},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"is_oa":true,"landing_page_url":"https://doi.org/10.3390/a16050226","pdf_url":"https://www.mdpi.com/1999-4893/16/5/226/pdf?version=1682590965","source":{"id":"https://openalex.org/S190629608","display_name":"Algorithms","issn_l":"1999-4893","issn":["1999-4893"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true},{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2207.09139","pdf_url":"https://arxiv.org/pdf/2207.09139","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.3390/a16050226","pdf_url":"https://www.mdpi.com/1999-4893/16/5/226/pdf?version=1682590965","source":{"id":"https://openalex.org/S190629608","display_name":"Algorithms","issn_l":"1999-4893","issn":["1999-4893"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true},"sustainable_development_goals":[],"grants":[{"funder":"https://openalex.org/F4320324099","funder_display_name":"Russian Science Foundation","award_id":"21-11-00116"}],"datasets":[],"versions":[],"referenced_works_count":59,"referenced_works":["https://openalex.org/W1516659296","https://openalex.org/W1971713783","https://openalex.org/W1986614398","https://openalex.org/W1994857208","https://openalex.org/W2042410977","https://openalex.org/W2064903582","https://openalex.org/W2070493638","https://openalex.org/W2082681062","https://openalex.org/W2101626831","https://openalex.org/W2117308775","https://openalex.org/W2150291618","https://openalex.org/W2165698076","https://openalex.org/W2240609664","https://openalex.org/W2259222853","https://openalex.org/W2286642557","https://openalex.org/W2305754340","https://openalex.org/W2395579298","https://openalex.org/W2560821354","https://openalex.org/W2582129089","https://openalex.org/W2602173702","https://openalex.org/W2614165633","https://openalex.org/W2624816748","https://openalex.org/W2751077699","https://openalex.org/W2762552718","https://openalex.org/W2807340117","https://openalex.org/W2809303897","https://openalex.org/W2809468631","https://openalex.org/W2902340978","https://openalex.org/W2911964244","https://openalex.org/W2962727190","https://openalex.org/W2963331664","https://openalex.org/W2963371984","https://openalex.org/W2970278855","https://openalex.org/W2997876178","https://openalex.org/W3022396324","https://openalex.org/W3025378918","https://openalex.org/W3042126369","https://openalex.org/W3045303571","https://openalex.org/W3086090299","https://openalex.org/W3096295749","https://openalex.org/W3099692195","https://openalex.org/W3104676662","https://openalex.org/W3118918014","https://openalex.org/W3121909624","https://openalex.org/W3122126958","https://openalex.org/W3125272084","https://openalex.org/W3125459412","https://openalex.org/W3154782940","https://openalex.org/W3169597754","https://openalex.org/W3191067499","https://openalex.org/W3204398858","https://openalex.org/W3208088432","https://openalex.org/W3208624098","https://openalex.org/W3210609413","https://openalex.org/W4205459532","https://openalex.org/W4280512567","https://openalex.org/W4297263351","https://openalex.org/W4311714479","https://openalex.org/W75679243"],"related_works":["https://openalex.org/W4289356671","https://openalex.org/W3186837933","https://openalex.org/W3174513558","https://openalex.org/W2389155397","https://openalex.org/W2368989808","https://openalex.org/W2355687852","https://openalex.org/W2312753042","https://openalex.org/W2165884543","https://openalex.org/W2034959125","https://openalex.org/W1969346022"],"abstract_inverted_index":{"A":[0],"new":[1],"method":[2],"for":[3,23,50,171],"estimating":[4],"the":[5,28,31,39,47,70,109,113,117,124,130,151,165],"conditional":[6],"average":[7],"treatment":[8,58,177],"effect":[9],"is":[10,16,35,43,65,86,136,187],"proposed":[11,134,183],"in":[12,129],"this":[13],"paper.":[14],"It":[15],"called":[17],"TNW-CATE":[18,45,64,160,186],"(the":[19],"Trainable":[20],"Nadaraya\u2013Watson":[21,48,71,118],"regression":[22,49,72],"CATE)":[24],"and":[25,38,57,90,145,161,169,176],"based":[26],"on":[27,88],"assumption":[29],"that":[30,105],"number":[32,40],"of":[33,41,53,69,80,98,143,174,182],"controls":[34],"rather":[36],"large":[37],"treatments":[42],"small.":[44],"uses":[46],"predicting":[51],"outcomes":[52],"patients":[54],"from":[55],"control":[56,175],"groups.":[59],"The":[60,84,120,133,180],"main":[61],"idea":[62],"behind":[63],"to":[66,138],"train":[67],"kernels":[68,94],"by":[73],"using":[74],"a":[75,81,96],"weight":[76],"sharing":[77],"neural":[78,99],"network":[79,85,115,121],"specific":[82],"form.":[83],"trained":[87],"controls,":[89],"it":[91,163],"replaces":[92],"standard":[93],"with":[95,101,164],"set":[97],"subnetworks":[100],"shared":[102],"parameters":[103],"such":[104],"every":[106],"subnetwork":[107],"implements":[108,116],"trainable":[110],"kernel,":[111],"but":[112,150],"whole":[114],"estimator.":[119],"memorizes":[122],"how":[123],"feature":[125,131],"vectors":[126],"are":[127,148,153],"located":[128],"space.":[132],"approach":[135],"similar":[137],"transfer":[139],"learning":[140],"when":[141],"domains":[142],"source":[144],"target":[146],"data":[147],"similar,":[149],"tasks":[152],"different.":[154],"Various":[155],"numerical":[156],"simulation":[157],"experiments":[158],"illustrate":[159],"compare":[162],"well-known":[166],"T-learner,":[167],"S-learner,":[168],"X-learner":[170],"several":[172],"types":[173],"outcome":[178],"functions.":[179],"code":[181],"algorithms":[184],"implementing":[185],"publicly":[188],"available.":[189]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4367300158","counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2024-12-11T08:52:22.394076","created_date":"2023-04-29"}