{"id":"https://openalex.org/W4386066310","doi":"https://doi.org/10.1109/isit54713.2023.10206572","title":"Random linear estimation with rotationally-invariant designs: Asymptotics at high temperature","display_name":"Random linear estimation with rotationally-invariant designs: Asymptotics at high temperature","publication_year":2023,"publication_date":"2023-06-25","ids":{"openalex":"https://openalex.org/W4386066310","doi":"https://doi.org/10.1109/isit54713.2023.10206572"},"language":"en","primary_location":{"id":"doi:10.1109/isit54713.2023.10206572","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit54713.2023.10206572","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Symposium on Information Theory (ISIT)","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/A5101860136","display_name":"Yufan Li","orcid":"https://orcid.org/0009-0009-7080-1544"},"institutions":[{"id":"https://openalex.org/I2801851002","display_name":"Harvard University Press","ror":"https://ror.org/006v7bf86","country_code":"US","type":"other","lineage":["https://openalex.org/I136199984","https://openalex.org/I2801851002"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yufan Li","raw_affiliation_strings":["Harvard University,Cambridge,MA,02138"],"affiliations":[{"raw_affiliation_string":"Harvard University,Cambridge,MA,02138","institution_ids":["https://openalex.org/I2801851002"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047187143","display_name":"Zhou Fan","orcid":"https://orcid.org/0000-0002-5940-4697"},"institutions":[{"id":"https://openalex.org/I32971472","display_name":"Yale University","ror":"https://ror.org/03v76x132","country_code":"US","type":"education","lineage":["https://openalex.org/I32971472"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhou Fan","raw_affiliation_strings":["Yale University,New Haven,CT,06511"],"affiliations":[{"raw_affiliation_string":"Yale University,New Haven,CT,06511","institution_ids":["https://openalex.org/I32971472"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114832181","display_name":"Subhabrata Sen","orcid":"https://orcid.org/0009-0005-5969-1023"},"institutions":[{"id":"https://openalex.org/I2801851002","display_name":"Harvard University Press","ror":"https://ror.org/006v7bf86","country_code":"US","type":"other","lineage":["https://openalex.org/I136199984","https://openalex.org/I2801851002"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Subhabrata Sen","raw_affiliation_strings":["Harvard University,Cambridge,MA,02138"],"affiliations":[{"raw_affiliation_string":"Harvard University,Cambridge,MA,02138","institution_ids":["https://openalex.org/I2801851002"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100645159","display_name":"Yihong Wu","orcid":"https://orcid.org/0000-0001-9239-7671"},"institutions":[{"id":"https://openalex.org/I32971472","display_name":"Yale University","ror":"https://ror.org/03v76x132","country_code":"US","type":"education","lineage":["https://openalex.org/I32971472"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yihong Wu","raw_affiliation_strings":["Yale University,New Haven,CT,06511"],"affiliations":[{"raw_affiliation_string":"Yale University,New Haven,CT,06511","institution_ids":["https://openalex.org/I32971472"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101860136"],"corresponding_institution_ids":["https://openalex.org/I2801851002"],"apc_list":null,"apc_paid":null,"fwci":1.0421,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.78209952,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"156","last_page":"161"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9987999796867371,"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":0.9987999796867371,"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/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9958000183105469,"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/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.9789999723434448,"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/invariant","display_name":"Invariant (physics)","score":0.5077996850013733},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.5075668096542358},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4798676371574402},{"id":"https://openalex.org/keywords/bayes-theorem","display_name":"Bayes' theorem","score":0.4523063004016876},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.39861950278282166},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.3603261709213257},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.3549126386642456},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.33483558893203735},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.22066569328308105},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.21009701490402222},{"id":"https://openalex.org/keywords/mathematical-physics","display_name":"Mathematical physics","score":0.08019107580184937}],"concepts":[{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.5077996850013733},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.5075668096542358},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4798676371574402},{"id":"https://openalex.org/C207201462","wikidata":"https://www.wikidata.org/wiki/Q182505","display_name":"Bayes' theorem","level":3,"score":0.4523063004016876},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.39861950278282166},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.3603261709213257},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.3549126386642456},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.33483558893203735},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.22066569328308105},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.21009701490402222},{"id":"https://openalex.org/C37914503","wikidata":"https://www.wikidata.org/wiki/Q156495","display_name":"Mathematical physics","level":1,"score":0.08019107580184937}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isit54713.2023.10206572","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit54713.2023.10206572","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Symposium on Information Theory (ISIT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.7799999713897705,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W653925602","https://openalex.org/W2032230252","https://openalex.org/W2055984460","https://openalex.org/W2073521724","https://openalex.org/W2081785908","https://openalex.org/W2086979092","https://openalex.org/W2087603457","https://openalex.org/W2101435685","https://openalex.org/W2111616148","https://openalex.org/W2116394223","https://openalex.org/W2135859872","https://openalex.org/W2138358551","https://openalex.org/W2160051394","https://openalex.org/W2161410247","https://openalex.org/W2167783913","https://openalex.org/W2483978192","https://openalex.org/W2788412124","https://openalex.org/W2918745211","https://openalex.org/W2945463326","https://openalex.org/W2950135859","https://openalex.org/W2963279235","https://openalex.org/W2963602028","https://openalex.org/W2963639053","https://openalex.org/W2963698262","https://openalex.org/W2963765569","https://openalex.org/W2974583905","https://openalex.org/W3009717121","https://openalex.org/W3023628608","https://openalex.org/W3098725392","https://openalex.org/W3099090856","https://openalex.org/W3103257261","https://openalex.org/W3104520293","https://openalex.org/W3159790704","https://openalex.org/W3198149474","https://openalex.org/W3209278616","https://openalex.org/W4226147086","https://openalex.org/W4248709896","https://openalex.org/W4285210099","https://openalex.org/W4289713185","https://openalex.org/W4293867785","https://openalex.org/W4383852434","https://openalex.org/W6681107968","https://openalex.org/W6754890952","https://openalex.org/W6782558979","https://openalex.org/W6794596340","https://openalex.org/W6803652093","https://openalex.org/W6810327052","https://openalex.org/W6810587743"],"related_works":["https://openalex.org/W2580650124","https://openalex.org/W4386190339","https://openalex.org/W2968424575","https://openalex.org/W3142333283","https://openalex.org/W3122088529","https://openalex.org/W2085259108","https://openalex.org/W3041320102","https://openalex.org/W2343819364","https://openalex.org/W2133205540","https://openalex.org/W2046798682"],"abstract_inverted_index":{"We":[0],"study":[1],"estimation":[2],"in":[3,15,35],"the":[4,30,38,58,72,108,130,136,142],"linear":[5],"model":[6],"y":[7],"=":[8],"A\u03b2":[9],"<sup":[10,21,78,114],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[11,22,79,115],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">\u22c6</sup>":[12,23,80],"+":[13],"\u03f5,":[14],"a":[16,49,90,103,121,133],"Bayesian":[17],"setting":[18],"where":[19,126],"\u03b2":[20,77],"has":[24],"an":[25],"entrywise":[26],"i.i.d.":[27],"prior":[28],"and":[29,44,66,96],"design":[31],"A":[32,113],"is":[33],"rotationally-invariant":[34,99],"law.":[36],"In":[37,82],"large":[39],"system":[40],"limit":[41],"as":[42],"dimension":[43],"sample":[45],"size":[46],"increase":[47],"proportionally,":[48],"set":[50],"of":[51,76,93,110,112,132,135],"related":[52],"conjectures":[53,88],"have":[54],"been":[55],"postulated":[56],"for":[57,89,97,140],"asymptotic":[59],"mutual":[60],"information,":[61],"Bayes-optimal":[62],"mean":[63,75],"squared":[64],"error,":[65],"TAP":[67,143],"mean-field":[68,144],"equations":[69],"that":[70,106],"characterize":[71],"Bayes":[73],"posterior":[74],".":[81],"this":[83],"work,":[84],"we":[85,127],"prove":[86],"these":[87],"general":[91],"class":[92],"signal":[94],"priors":[95],"arbitrary":[98],"designs":[100],"A,":[101],"under":[102],"\"high-temperature\"":[104],"condition":[105,128],"restricts":[107],"range":[109],"eigenvalues":[111],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">\u22a4</sup>":[116],"A.":[117],"Our":[118],"proof":[119],"uses":[120],"conditional":[122],"second-moment":[123],"method":[124],"argument,":[125],"on":[129],"iterates":[131],"version":[134],"Vector":[137],"AMP":[138],"algorithm":[139],"solving":[141],"equations.":[145]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}