{"id":"https://openalex.org/W4310489637","doi":"https://doi.org/10.1109/tsp.2022.3216704","title":"Two-Stage Robust and Sparse Distributed Statistical Inference for Large-Scale Data","display_name":"Two-Stage Robust and Sparse Distributed Statistical Inference for Large-Scale Data","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4310489637","doi":"https://doi.org/10.1109/tsp.2022.3216704"},"language":"en","primary_location":{"id":"doi:10.1109/tsp.2022.3216704","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2022.3216704","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"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 Transactions on Signal Processing","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/A5063148322","display_name":"Emadaldin Mozafari-Majd","orcid":"https://orcid.org/0000-0002-6319-9438"},"institutions":[{"id":"https://openalex.org/I9927081","display_name":"Aalto University","ror":"https://ror.org/020hwjq30","country_code":"FI","type":"education","lineage":["https://openalex.org/I9927081"]}],"countries":["FI"],"is_corresponding":true,"raw_author_name":"Emadaldin Mozafari-Majd","raw_affiliation_strings":["Department of Signal Processing and Acoustics, Aalto University, Aalto, Finland"],"affiliations":[{"raw_affiliation_string":"Department of Signal Processing and Acoustics, Aalto University, Aalto, Finland","institution_ids":["https://openalex.org/I9927081"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5105267090","display_name":"Visa Koivunen","orcid":"https://orcid.org/0000-0003-1454-5928"},"institutions":[{"id":"https://openalex.org/I9927081","display_name":"Aalto University","ror":"https://ror.org/020hwjq30","country_code":"FI","type":"education","lineage":["https://openalex.org/I9927081"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Visa Koivunen","raw_affiliation_strings":["Department of Signal Processing and Acoustics, Aalto University, Aalto, Finland"],"affiliations":[{"raw_affiliation_string":"Department of Signal Processing and Acoustics, Aalto University, Aalto, Finland","institution_ids":["https://openalex.org/I9927081"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5063148322"],"corresponding_institution_ids":["https://openalex.org/I9927081"],"apc_list":null,"apc_paid":null,"fwci":0.7294,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.72894284,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":"70","issue":null,"first_page":"5351","last_page":"5365"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9995999932289124,"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":0.9995999932289124,"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/T11871","display_name":"Advanced Statistical Methods and Models","score":0.996999979019165,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9944999814033508,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/robustness","display_name":"Robustness (evolution)","score":0.6276938319206238},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.6047144532203674},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5842394232749939},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5745357871055603},{"id":"https://openalex.org/keywords/statistical-inference","display_name":"Statistical inference","score":0.5049508213996887},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.4799092710018158},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.463552862405777},{"id":"https://openalex.org/keywords/robust-statistics","display_name":"Robust statistics","score":0.42654553055763245},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3270108699798584},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.32540518045425415},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2847781777381897},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2486276924610138}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6276938319206238},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.6047144532203674},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5842394232749939},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5745357871055603},{"id":"https://openalex.org/C134261354","wikidata":"https://www.wikidata.org/wiki/Q938438","display_name":"Statistical inference","level":2,"score":0.5049508213996887},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.4799092710018158},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.463552862405777},{"id":"https://openalex.org/C67226441","wikidata":"https://www.wikidata.org/wiki/Q1665389","display_name":"Robust statistics","level":3,"score":0.42654553055763245},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3270108699798584},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.32540518045425415},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2847781777381897},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2486276924610138},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tsp.2022.3216704","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2022.3216704","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"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 Transactions on Signal Processing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321108","display_name":"Academy of Finland","ror":"https://ror.org/05k73zm37"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":60,"referenced_works":["https://openalex.org/W68270097","https://openalex.org/W160307228","https://openalex.org/W1535995764","https://openalex.org/W1551360398","https://openalex.org/W1585351680","https://openalex.org/W1969936152","https://openalex.org/W1995119847","https://openalex.org/W2009462809","https://openalex.org/W2009891346","https://openalex.org/W2020788727","https://openalex.org/W2039385587","https://openalex.org/W2039943102","https://openalex.org/W2050551672","https://openalex.org/W2051245758","https://openalex.org/W2058240339","https://openalex.org/W2069119359","https://openalex.org/W2097209031","https://openalex.org/W2099238445","https://openalex.org/W2109177042","https://openalex.org/W2109837871","https://openalex.org/W2114255896","https://openalex.org/W2128235479","https://openalex.org/W2128899793","https://openalex.org/W2135046866","https://openalex.org/W2141556672","https://openalex.org/W2146550217","https://openalex.org/W2146774335","https://openalex.org/W2147606185","https://openalex.org/W2160222246","https://openalex.org/W2168175751","https://openalex.org/W2168189541","https://openalex.org/W2172185584","https://openalex.org/W2291895482","https://openalex.org/W2302063474","https://openalex.org/W2330829943","https://openalex.org/W2787771020","https://openalex.org/W2963705952","https://openalex.org/W2963786589","https://openalex.org/W2964037952","https://openalex.org/W2990681736","https://openalex.org/W3010391499","https://openalex.org/W3010770828","https://openalex.org/W3099470970","https://openalex.org/W3102311896","https://openalex.org/W3102479286","https://openalex.org/W3102726611","https://openalex.org/W3103324688","https://openalex.org/W3103643510","https://openalex.org/W3104020845","https://openalex.org/W3104444713","https://openalex.org/W3106369002","https://openalex.org/W3165074335","https://openalex.org/W3209754817","https://openalex.org/W4249947721","https://openalex.org/W6606457585","https://openalex.org/W6634802981","https://openalex.org/W6679265385","https://openalex.org/W6684962594","https://openalex.org/W6696350760","https://openalex.org/W6770600427"],"related_works":["https://openalex.org/W2046343964","https://openalex.org/W137830373","https://openalex.org/W4379515847","https://openalex.org/W2216963642","https://openalex.org/W3000984192","https://openalex.org/W2283061017","https://openalex.org/W4210897550","https://openalex.org/W2107646698","https://openalex.org/W1539940077","https://openalex.org/W1600426151"],"abstract_inverted_index":{"In":[0,55,112],"this":[1],"paper,":[2],"we":[3,162],"address":[4],"the":[5,30,56,74,95,99,105,113,116,144,152,164,169],"problem":[6],"of":[7,29,77,146,168,182,208],"conducting":[8],"statistical":[9,45,166],"inference":[10,46,129,148,192],"in":[11,108,199],"settings":[12],"involving":[13],"large-scale":[14],"data":[15,31,101,213],"that":[16],"may":[17],"be":[18],"high-dimensional":[19,50,215],"and":[20,27,35,43,120,136,155,171,184,190,197,205,216],"contaminated":[21,217],"by":[22,52,68,89,218],"outliers.":[23,219],"The":[24,79,127,186],"high":[25],"volume":[26],"dimensionality":[28],"require":[32],"distributed":[33,42,191],"processing":[34],"storage":[36],"solutions.":[37],"We":[38],"propose":[39],"a":[40,90,109,179],"two-stage":[41,188],"robust":[44,70,110,119,170,189],"procedures":[47,193],"coping":[48],"with":[49],"models":[51],"promoting":[53],"sparsity.":[54],"first":[57],"stage,":[58,115],"known":[59],"as":[60],"model":[61],"selection,":[62,201],"relevant":[63,106],"predictors":[64],"are":[65,86,125,149],"locally":[66],"selected":[67],"applying":[69],"Lasso":[71],"estimators":[72],"to":[73,93,141,151],"distinct":[75],"subsets":[76],"data.":[78],"variable":[80,200],"selections":[81],"from":[82],"each":[83],"computation":[84],"node":[85],"then":[87],"fused":[88],"voting":[91],"scheme":[92],"find":[94],"sparse":[96],"basis":[97],"for":[98,178],"complete":[100],"set.":[102],"It":[103],"identifies":[104],"variables":[107],"manner.":[111],"second":[114],"developed":[117],"statistically":[118],"computationally":[121,172],"efficient":[122,173],"bootstrap":[123,174,206],"methods":[124,175],"employed.":[126],"actual":[128],"constructs":[130],"confidence":[131,203],"intervals,":[132],"finds":[133],"parameter":[134],"estimates":[135],"quantifies":[137],"standard":[138,209],"deviation.":[139],"Similar":[140],"stage":[142],"1,":[143],"results":[145],"local":[147],"communicated":[150],"fusion":[153],"center":[154],"combined":[156],"there.":[157],"By":[158],"using":[159],"analytical":[160],"methods,":[161],"establish":[163],"favorable":[165],"properties":[167],"including":[176],"consistency":[177],"fixed":[180],"number":[181],"predictors,":[183],"robustness.":[185],"proposed":[187],"demonstrate":[194],"reliable":[195],"performance":[196],"robustness":[198],"finding":[202],"intervals":[204],"approximations":[207],"deviations":[210],"even":[211],"when":[212],"is":[214]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2022-12-11T00:00:00"}