{"id":"https://openalex.org/W3016604095","doi":"https://doi.org/10.1109/isit44484.2020.9174104","title":"High-dimensional rank-one nonsymmetric matrix decomposition: the spherical case","display_name":"High-dimensional rank-one nonsymmetric matrix decomposition: the spherical case","publication_year":2020,"publication_date":"2020-06-01","ids":{"openalex":"https://openalex.org/W3016604095","doi":"https://doi.org/10.1109/isit44484.2020.9174104","mag":"3016604095"},"language":"en","primary_location":{"id":"doi:10.1109/isit44484.2020.9174104","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit44484.2020.9174104","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Symposium on Information Theory (ISIT)","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2004.06975","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Cl\u00e9ment Luneau","orcid":null},"institutions":[{"id":"https://openalex.org/I5124864","display_name":"\u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne","ror":"https://ror.org/02s376052","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I5124864"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Cl\u00e9ment Luneau","raw_affiliation_strings":["&#x00C9;cole Polytechnique F&#x00E9;d&#x00E9;rale de Lausanne"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"&#x00C9;cole Polytechnique F&#x00E9;d&#x00E9;rale de Lausanne","institution_ids":["https://openalex.org/I5124864"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Nicolas Macris","orcid":null},"institutions":[{"id":"https://openalex.org/I5124864","display_name":"\u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne","ror":"https://ror.org/02s376052","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I5124864"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Nicolas Macris","raw_affiliation_strings":["&#x00C9;cole Polytechnique F&#x00E9;d&#x00E9;rale de Lausanne"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"&#x00C9;cole Polytechnique F&#x00E9;d&#x00E9;rale de Lausanne","institution_ids":["https://openalex.org/I5124864"]}]},{"author_position":"last","author":{"id":null,"display_name":"Jean Barbier","orcid":null},"institutions":[{"id":"https://openalex.org/I3019243323","display_name":"Center for Theoretical Physics","ror":"https://ror.org/04kfyt897","country_code":"PL","type":"facility","lineage":["https://openalex.org/I3019243323","https://openalex.org/I99542240"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Jean Barbier","raw_affiliation_strings":["The Abdus Salam International Center for Theoretical Physics"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Abdus Salam International Center for Theoretical Physics","institution_ids":["https://openalex.org/I3019243323"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.5382,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.81540342,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"2646","last_page":"2651"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12303","display_name":"Tensor decomposition and applications","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T12303","display_name":"Tensor decomposition and applications","score":0.9998000264167786,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9997000098228455,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9969000220298767,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.6026999950408936},{"id":"https://openalex.org/keywords/independent-and-identically-distributed-random-variables","display_name":"Independent and identically distributed random variables","score":0.5333999991416931},{"id":"https://openalex.org/keywords/product","display_name":"Product (mathematics)","score":0.5015000104904175},{"id":"https://openalex.org/keywords/outer-product","display_name":"Outer product","score":0.45399999618530273},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.43299999833106995},{"id":"https://openalex.org/keywords/tensor-product","display_name":"Tensor product","score":0.3873000144958496},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.3864000141620636}],"concepts":[{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.6564000248908997},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.6026999950408936},{"id":"https://openalex.org/C141513077","wikidata":"https://www.wikidata.org/wiki/Q378542","display_name":"Independent and identically distributed random variables","level":3,"score":0.5333999991416931},{"id":"https://openalex.org/C90673727","wikidata":"https://www.wikidata.org/wiki/Q901718","display_name":"Product (mathematics)","level":2,"score":0.5015000104904175},{"id":"https://openalex.org/C180623205","wikidata":"https://www.wikidata.org/wiki/Q1268589","display_name":"Outer product","level":3,"score":0.45399999618530273},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.43299999833106995},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.41280001401901245},{"id":"https://openalex.org/C51255310","wikidata":"https://www.wikidata.org/wiki/Q1163016","display_name":"Tensor product","level":2,"score":0.3873000144958496},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.3864000141620636},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.3580999970436096},{"id":"https://openalex.org/C2988995629","wikidata":"https://www.wikidata.org/wiki/Q2915729","display_name":"Matrix algebra","level":3,"score":0.3215999901294708},{"id":"https://openalex.org/C126412783","wikidata":"https://www.wikidata.org/wiki/Q15104431","display_name":"Tensor operator","level":3,"score":0.3174999952316284},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.3050999939441681},{"id":"https://openalex.org/C84316537","wikidata":"https://www.wikidata.org/wiki/Q36255","display_name":"Unit vector","level":2,"score":0.2890999913215637},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.2865000069141388},{"id":"https://openalex.org/C54848796","wikidata":"https://www.wikidata.org/wiki/Q339011","display_name":"Symmetric matrix","level":3,"score":0.2662000060081482},{"id":"https://openalex.org/C17349429","wikidata":"https://www.wikidata.org/wiki/Q1049914","display_name":"Matrix multiplication","level":3,"score":0.25920000672340393},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.25600001215934753},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.2533999979496002}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/isit44484.2020.9174104","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit44484.2020.9174104","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Symposium on Information Theory (ISIT)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2004.06975","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2004.06975","pdf_url":"https://arxiv.org/pdf/2004.06975","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"},{"id":"pmh:oai:infoscience.epfl.ch:290756","is_oa":true,"landing_page_url":"https://infoscience.epfl.ch/handle/20.500.14299/183882","pdf_url":null,"source":{"id":"https://openalex.org/S4306400487","display_name":"Infoscience (Ecole Polytechnique F\u00e9d\u00e9rale de Lausanne)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"WoS","raw_type":"conference proceedings"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2004.06975","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2004.06975","pdf_url":"https://arxiv.org/pdf/2004.06975","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":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1659832490","https://openalex.org/W1964458748","https://openalex.org/W1978864992","https://openalex.org/W1983383403","https://openalex.org/W2024165284","https://openalex.org/W2031399827","https://openalex.org/W2079822812","https://openalex.org/W2088593317","https://openalex.org/W2099551908","https://openalex.org/W2111616148","https://openalex.org/W2119412403","https://openalex.org/W2161410247","https://openalex.org/W2258054274","https://openalex.org/W2469230926","https://openalex.org/W2571114381","https://openalex.org/W2588219153","https://openalex.org/W2913003253","https://openalex.org/W2918745211","https://openalex.org/W2963215260","https://openalex.org/W3016604095","https://openalex.org/W3106533591","https://openalex.org/W6735974756","https://openalex.org/W6737355649","https://openalex.org/W6754335476","https://openalex.org/W6763058560","https://openalex.org/W6765981223"],"related_works":[],"abstract_inverted_index":{"We":[0,45],"consider":[1],"the":[2,23,33,51,59,62],"problem":[3],"of":[4,26],"estimating":[5],"a":[6,47],"rank-one":[7,86],"nonsymmetric":[8],"matrix":[9,16],"under":[10],"additive":[11],"white":[12],"Gaussian":[13],"noise.":[14],"The":[15,79],"to":[17,85],"estimate":[18],"can":[19,82],"be":[20,83],"written":[21],"as":[22],"outer":[24],"product":[25],"two":[27],"vectors":[28,39,57,72],"and":[29,58,75],"we":[30],"look":[31],"at":[32],"special":[34],"case":[35],"in":[36,61],"which":[37,70],"both":[38],"are":[40],"uniformly":[41],"distributed":[42,77],"on":[43],"spheres.":[44],"prove":[46],"replica-symmetric":[48],"formula":[49],"for":[50],"average":[52],"mutual":[53],"information":[54],"between":[55],"these":[56],"observations":[60],"high-dimensional":[63],"regime.":[64],"This":[65],"goes":[66],"beyond":[67],"previous":[68],"results":[69],"considered":[71],"with":[73],"independent":[74],"identically":[76],"elements.":[78],"method":[80],"used":[81],"extended":[84],"tensor":[87],"problems.":[88]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2020-04-24T00:00:00"}
