{"id":"https://openalex.org/W3168763471","doi":"https://doi.org/10.1109/ieeeconf53345.2021.9723149","title":"A Minimax Lower Bound for Low-Rank Matrix-Variate Logistic Regression","display_name":"A Minimax Lower Bound for Low-Rank Matrix-Variate Logistic Regression","publication_year":2021,"publication_date":"2021-10-31","ids":{"openalex":"https://openalex.org/W3168763471","doi":"https://doi.org/10.1109/ieeeconf53345.2021.9723149","mag":"3168763471"},"language":"en","primary_location":{"id":"doi:10.1109/ieeeconf53345.2021.9723149","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ieeeconf53345.2021.9723149","pdf_url":null,"source":{"id":"https://openalex.org/S4363607877","display_name":"2021 55th Asilomar Conference on Signals, Systems, and Computers","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 55th Asilomar Conference on Signals, Systems, and Computers","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2105.14673","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5044518805","display_name":"Batoul Taki","orcid":null},"institutions":[{"id":"https://openalex.org/I102322142","display_name":"Rutgers, The State University of New Jersey","ror":"https://ror.org/05vt9qd57","country_code":"US","type":"education","lineage":["https://openalex.org/I102322142"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Batoul Taki","raw_affiliation_strings":["Rutgers University&#x2013;New Brunswick,Department of Electrical and Computer Engineering,Piscataway,NJ"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rutgers University&#x2013;New Brunswick,Department of Electrical and Computer Engineering,Piscataway,NJ","institution_ids":["https://openalex.org/I102322142"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000040402","display_name":"Mohsen Ghassemi","orcid":"https://orcid.org/0000-0003-4049-7827"},"institutions":[{"id":"https://openalex.org/I102322142","display_name":"Rutgers, The State University of New Jersey","ror":"https://ror.org/05vt9qd57","country_code":"US","type":"education","lineage":["https://openalex.org/I102322142"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mohsen Ghassemi","raw_affiliation_strings":["Rutgers University&#x2013;New Brunswick,Department of Electrical and Computer Engineering,Piscataway,NJ"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rutgers University&#x2013;New Brunswick,Department of Electrical and Computer Engineering,Piscataway,NJ","institution_ids":["https://openalex.org/I102322142"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087162046","display_name":"Anand D. Sarwate","orcid":"https://orcid.org/0000-0001-6123-5282"},"institutions":[{"id":"https://openalex.org/I102322142","display_name":"Rutgers, The State University of New Jersey","ror":"https://ror.org/05vt9qd57","country_code":"US","type":"education","lineage":["https://openalex.org/I102322142"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Anand D. Sarwate","raw_affiliation_strings":["Rutgers University&#x2013;New Brunswick,Department of Electrical and Computer Engineering,Piscataway,NJ"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rutgers University&#x2013;New Brunswick,Department of Electrical and Computer Engineering,Piscataway,NJ","institution_ids":["https://openalex.org/I102322142"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5028718006","display_name":"Waheed U. Bajwa","orcid":"https://orcid.org/0000-0003-4406-5263"},"institutions":[{"id":"https://openalex.org/I102322142","display_name":"Rutgers, The State University of New Jersey","ror":"https://ror.org/05vt9qd57","country_code":"US","type":"education","lineage":["https://openalex.org/I102322142"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Waheed U. Bajwa","raw_affiliation_strings":["Rutgers University&#x2013;New Brunswick,Department of Electrical and Computer Engineering,Piscataway,NJ"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rutgers University&#x2013;New Brunswick,Department of Electrical and Computer Engineering,Piscataway,NJ","institution_ids":["https://openalex.org/I102322142"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4919,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.79632353,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"477","last_page":"484"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998000264167786,"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"}},{"id":"https://openalex.org/T12303","display_name":"Tensor decomposition and applications","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2605","display_name":"Computational Mathematics"},"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/T10136","display_name":"Statistical Methods and Inference","score":0.9916999936103821,"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/random-variate","display_name":"Random variate","score":0.7247782349586487},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.7049030065536499},{"id":"https://openalex.org/keywords/logistic-regression","display_name":"Logistic regression","score":0.7042348384857178},{"id":"https://openalex.org/keywords/minimax","display_name":"Minimax","score":0.6853981614112854},{"id":"https://openalex.org/keywords/multinomial-logistic-regression","display_name":"Multinomial logistic regression","score":0.6639590263366699},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.5608698129653931},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.5356329083442688},{"id":"https://openalex.org/keywords/logistic-distribution","display_name":"Logistic distribution","score":0.5164975523948669},{"id":"https://openalex.org/keywords/upper-and-lower-bounds","display_name":"Upper and lower bounds","score":0.5124359726905823},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.4806467592716217},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.4227692484855652},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.3582686483860016},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.3090249300003052},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.24194613099098206},{"id":"https://openalex.org/keywords/random-variable","display_name":"Random variable","score":0.2292310893535614},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.08475151658058167}],"concepts":[{"id":"https://openalex.org/C141547133","wikidata":"https://www.wikidata.org/wiki/Q7291996","display_name":"Random variate","level":3,"score":0.7247782349586487},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.7049030065536499},{"id":"https://openalex.org/C151956035","wikidata":"https://www.wikidata.org/wiki/Q1132755","display_name":"Logistic regression","level":2,"score":0.7042348384857178},{"id":"https://openalex.org/C149728462","wikidata":"https://www.wikidata.org/wiki/Q751319","display_name":"Minimax","level":2,"score":0.6853981614112854},{"id":"https://openalex.org/C117568660","wikidata":"https://www.wikidata.org/wiki/Q1650843","display_name":"Multinomial logistic regression","level":2,"score":0.6639590263366699},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.5608698129653931},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.5356329083442688},{"id":"https://openalex.org/C94465730","wikidata":"https://www.wikidata.org/wiki/Q589603","display_name":"Logistic distribution","level":3,"score":0.5164975523948669},{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.5124359726905823},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.4806467592716217},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.4227692484855652},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.3582686483860016},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.3090249300003052},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.24194613099098206},{"id":"https://openalex.org/C122123141","wikidata":"https://www.wikidata.org/wiki/Q176623","display_name":"Random variable","level":2,"score":0.2292310893535614},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.08475151658058167},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/ieeeconf53345.2021.9723149","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ieeeconf53345.2021.9723149","pdf_url":null,"source":{"id":"https://openalex.org/S4363607877","display_name":"2021 55th Asilomar Conference on Signals, Systems, and Computers","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 55th Asilomar Conference on Signals, Systems, and Computers","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2105.14673","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2105.14673","pdf_url":"https://arxiv.org/pdf/2105.14673","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":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2105.14673","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2105.14673","pdf_url":"https://arxiv.org/pdf/2105.14673","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":[],"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":[{"score":0.5899999737739563,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W1538452572","https://openalex.org/W1630816465","https://openalex.org/W1989274820","https://openalex.org/W2024165284","https://openalex.org/W2025183578","https://openalex.org/W2099111195","https://openalex.org/W2111297856","https://openalex.org/W2138806521","https://openalex.org/W2141556672","https://openalex.org/W2154152198","https://openalex.org/W2210387432","https://openalex.org/W2400617046","https://openalex.org/W2496316373","https://openalex.org/W2523452257","https://openalex.org/W2768292343","https://openalex.org/W2795040388","https://openalex.org/W2962806897","https://openalex.org/W2963548292","https://openalex.org/W2963924474","https://openalex.org/W2964357478","https://openalex.org/W2978570729","https://openalex.org/W3008292930","https://openalex.org/W3033283747","https://openalex.org/W3037072982","https://openalex.org/W3037843525","https://openalex.org/W3105524276","https://openalex.org/W3106435818","https://openalex.org/W4288095374","https://openalex.org/W6676665419","https://openalex.org/W6683117370","https://openalex.org/W6750111029","https://openalex.org/W6768894898","https://openalex.org/W6774374946","https://openalex.org/W6779691819"],"related_works":["https://openalex.org/W4236196231","https://openalex.org/W4285613942","https://openalex.org/W2159230091","https://openalex.org/W4248368593","https://openalex.org/W3118520592","https://openalex.org/W766138655","https://openalex.org/W129344463","https://openalex.org/W1901486481","https://openalex.org/W4246416652","https://openalex.org/W2289690891"],"abstract_inverted_index":{"This":[0,9],"paper":[1,10],"considers":[2],"the":[3,12,22,32,40,45,47,52,56,66,72,76,80,104],"problem":[4,25,85],"of":[5,44,51,58,69,79,108],"matrix-variate":[6],"logistic":[7,23,83,93,114],"regression.":[8,94],"derives":[11],"fundamental":[13],"error":[14],"threshold":[15],"on":[16,31,39],"estimating":[17],"low-rank":[18,81],"coefficient":[19,53],"matrices":[20],"in":[21,71,99],"regression":[24,84,115],"by":[26],"deriving":[27],"a":[28],"lower":[29,88,110],"bound":[30,36,62],"minimax":[33,109],"risk.":[34],"The":[35,60,95],"depends":[37],"explicitly":[38],"dimension":[41],"and":[42,49,55],"distribution":[43],"covariates,":[46],"rank":[48],"energy":[50],"matrix,":[54],"number":[57],"samples.":[59],"resulting":[61],"is":[63],"proportional":[64],"to":[65],"intrinsic":[67],"degrees":[68],"freedom":[70],"problem,":[73],"which":[74],"suggests":[75],"sample":[77],"complexity":[78],"matrix":[82],"can":[86],"be":[87],"than":[89],"that":[90],"for":[91,106,112],"vectorized":[92],"proof":[96],"techniques":[97],"utilized":[98],"this":[100],"work":[101],"also":[102],"set":[103],"stage":[105],"development":[107],"bounds":[111],"tensor-variate":[113],"problems.":[116]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2021,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
