{"id":"https://openalex.org/W3195378702","doi":"https://doi.org/10.1109/ssp49050.2021.9513852","title":"Post-Parameter-Selection Maximum-Likelihood Estimation","display_name":"Post-Parameter-Selection Maximum-Likelihood Estimation","publication_year":2021,"publication_date":"2021-07-11","ids":{"openalex":"https://openalex.org/W3195378702","doi":"https://doi.org/10.1109/ssp49050.2021.9513852","mag":"3195378702"},"language":"en","primary_location":{"id":"doi:10.1109/ssp49050.2021.9513852","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssp49050.2021.9513852","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE Statistical Signal Processing Workshop (SSP)","raw_type":"proceedings-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/A5009524494","display_name":"Nadav Harel","orcid":"https://orcid.org/0000-0001-5104-2786"},"institutions":[{"id":"https://openalex.org/I124227911","display_name":"Ben-Gurion University of the Negev","ror":"https://ror.org/05tkyf982","country_code":"IL","type":"education","lineage":["https://openalex.org/I124227911"]}],"countries":["IL"],"is_corresponding":true,"raw_author_name":"Nadav Harel","raw_affiliation_strings":["Ben-Gurion University of the Negev,School of Electrical and Computer Engineering,Beer-Sheva,Israel,84105"],"affiliations":[{"raw_affiliation_string":"Ben-Gurion University of the Negev,School of Electrical and Computer Engineering,Beer-Sheva,Israel,84105","institution_ids":["https://openalex.org/I124227911"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061404840","display_name":"Tirza Routtenberg","orcid":"https://orcid.org/0000-0002-7238-7764"},"institutions":[{"id":"https://openalex.org/I124227911","display_name":"Ben-Gurion University of the Negev","ror":"https://ror.org/05tkyf982","country_code":"IL","type":"education","lineage":["https://openalex.org/I124227911"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Tirza Routtenberg","raw_affiliation_strings":["Ben-Gurion University of the Negev,School of Electrical and Computer Engineering,Beer-Sheva,Israel,84105"],"affiliations":[{"raw_affiliation_string":"Ben-Gurion University of the Negev,School of Electrical and Computer Engineering,Beer-Sheva,Israel,84105","institution_ids":["https://openalex.org/I124227911"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5009524494"],"corresponding_institution_ids":["https://openalex.org/I124227911"],"apc_list":null,"apc_paid":null,"fwci":0.2719,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.63029092,"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":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9991000294685364,"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/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9991000294685364,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10876","display_name":"Fault Detection and Control Systems","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.820365309715271},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.7533440589904785},{"id":"https://openalex.org/keywords/estimation-theory","display_name":"Estimation theory","score":0.5334985852241516},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5013706684112549},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.46138671040534973},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.4538026452064514},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.4338933825492859},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.4262840449810028},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.418984055519104},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.38963228464126587},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3707049489021301},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3398838937282562},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3108435273170471}],"concepts":[{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.820365309715271},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.7533440589904785},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.5334985852241516},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5013706684112549},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.46138671040534973},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.4538026452064514},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.4338933825492859},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.4262840449810028},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.418984055519104},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.38963228464126587},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3707049489021301},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3398838937282562},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3108435273170471}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ssp49050.2021.9513852","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssp49050.2021.9513852","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE Statistical Signal Processing Workshop (SSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W250076511","https://openalex.org/W1911249530","https://openalex.org/W1965392255","https://openalex.org/W1976709621","https://openalex.org/W2009462809","https://openalex.org/W2015810892","https://openalex.org/W2017137572","https://openalex.org/W2034260606","https://openalex.org/W2086236873","https://openalex.org/W2099756352","https://openalex.org/W2127327184","https://openalex.org/W2140856955","https://openalex.org/W2693498932","https://openalex.org/W2759547991","https://openalex.org/W2766201455","https://openalex.org/W2926365869","https://openalex.org/W2963469382","https://openalex.org/W3100410537","https://openalex.org/W3102311896","https://openalex.org/W3105340263","https://openalex.org/W3120319756","https://openalex.org/W3132596485","https://openalex.org/W3139737731","https://openalex.org/W4246784033","https://openalex.org/W4285719527","https://openalex.org/W4302561155","https://openalex.org/W6675074827"],"related_works":["https://openalex.org/W331019358","https://openalex.org/W4289539811","https://openalex.org/W2058283823","https://openalex.org/W4246838808","https://openalex.org/W2106362003","https://openalex.org/W2131062667","https://openalex.org/W773704376","https://openalex.org/W4207040961","https://openalex.org/W1968634768","https://openalex.org/W3125106038"],"abstract_inverted_index":{"Practical":[0],"multi-parameter":[1],"estimation":[2,23,44,54],"problems":[3],"with":[4,141],"limited":[5],"measurements":[6],"and":[7,34,80,93],"unidentifiable":[8],"scenarios":[9],"usually":[10],"involve":[11],"a":[12,47,62,105,129],"preliminary":[13],"data-based":[14,63],"selection":[15,147],"stage.":[16],"Recent":[17],"works":[18],"have":[19],"shown":[20],"that":[21,124],"selection-aware":[22],"methods":[24,45],"outperform":[25],"state-of-the-art":[26],"estimators":[27,86],"in":[28,98],"the":[29,56,69,73,76,81,88,108,117,125,133,142],"sense":[30],"of":[31,49,116],"post-selection":[32,35,77,85],"bias":[33],"mean-squared-error":[36],"(PSMSE).":[37],"In":[38],"this":[39],"paper,":[40],"we":[41,103],"discuss":[42],"non-Bayesian":[43],"where":[46],"subset":[48],"parameters":[50,90],"is":[51],"selected":[52],"for":[53,113,137],"from":[55],"full":[57],"unknown":[58],"parameter":[59],"vector":[60,139],"by":[61],"selection-rule.":[64],"We":[65],"present":[66],"four":[67],"estimators:":[68],"maximum":[70],"likelihood":[71],"(ML),":[72],"coherent":[74,82,118,134],"ML,":[75],"ML":[78,135],"(PSML),":[79],"PSML.":[83],"Coherent":[84],"force":[87],"unselected":[89],"to":[91],"zero,":[92],"thus,":[94],"can":[95],"be":[96],"implemented":[97],"practical":[99,114],"high-dimensional":[100],"problems.":[101],"Additionally,":[102],"develop":[104],"low-complexity":[106],"algorithm,":[107],"stochastic":[109],"approximation":[110],"PSML":[111,119],"(SA-PSML)":[112],"implementation":[115],"estimator.":[120],"Simulation":[121],"results":[122],"show":[123],"SA-PSML":[126],"algorithm":[127],"achieves":[128],"lower":[130],"PSMSE":[131],"than":[132],"estimator":[136],"sparse":[138],"recovery":[140],"orthogonal":[143],"matching":[144],"pursuit":[145],"(OMP)":[146],"rule.":[148]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}