{"id":"https://openalex.org/W2570974182","doi":"https://doi.org/10.1109/tit.2014.2368122","title":"Near Minimax Line Spectral Estimation","display_name":"Near Minimax Line Spectral Estimation","publication_year":2014,"publication_date":"2014-11-06","ids":{"openalex":"https://openalex.org/W2570974182","doi":"https://doi.org/10.1109/tit.2014.2368122","mag":"2570974182"},"language":"en","primary_location":{"id":"doi:10.1109/tit.2014.2368122","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tit.2014.2368122","pdf_url":null,"source":{"id":"https://openalex.org/S4502562","display_name":"IEEE Transactions on Information Theory","issn_l":"0018-9448","issn":["0018-9448","1557-9654"],"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 Information Theory","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/A5101848896","display_name":"Gongguo Tang","orcid":"https://orcid.org/0000-0002-7879-1338"},"institutions":[{"id":"https://openalex.org/I167576493","display_name":"Colorado School of Mines","ror":"https://ror.org/04raf6v53","country_code":"US","type":"education","lineage":["https://openalex.org/I167576493"]},{"id":"https://openalex.org/I135310074","display_name":"University of Wisconsin\u2013Madison","ror":"https://ror.org/01y2jtd41","country_code":"US","type":"education","lineage":["https://openalex.org/I135310074"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Gongguo Tang","raw_affiliation_strings":["Department of Electrical and Computer Science, Colorado School of Mines, Golden, CO, USA","University of Wisconsin\u2014Madison, Madison, WI, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Science, Colorado School of Mines, Golden, CO, USA","institution_ids":["https://openalex.org/I167576493"]},{"raw_affiliation_string":"University of Wisconsin\u2014Madison, Madison, WI, USA","institution_ids":["https://openalex.org/I135310074"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016309034","display_name":"Badri Narayan Bhaskar","orcid":null},"institutions":[{"id":"https://openalex.org/I135310074","display_name":"University of Wisconsin\u2013Madison","ror":"https://ror.org/01y2jtd41","country_code":"US","type":"education","lineage":["https://openalex.org/I135310074"]},{"id":"https://openalex.org/I4210134091","display_name":"Yahoo (United States)","ror":"https://ror.org/040dkzz12","country_code":"US","type":"company","lineage":["https://openalex.org/I4210134091"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Badri Narayan Bhaskar","raw_affiliation_strings":["University of Wisconsin\u2014Madison, Madison, WI, USA","Yahoo! Labs, Sunnyvale, CA, USA"],"affiliations":[{"raw_affiliation_string":"University of Wisconsin\u2014Madison, Madison, WI, USA","institution_ids":["https://openalex.org/I135310074"]},{"raw_affiliation_string":"Yahoo! Labs, Sunnyvale, CA, USA","institution_ids":["https://openalex.org/I4210134091"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012870568","display_name":"Benjamin Recht","orcid":"https://orcid.org/0000-0002-0293-593X"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]},{"id":"https://openalex.org/I135310074","display_name":"University of Wisconsin\u2013Madison","ror":"https://ror.org/01y2jtd41","country_code":"US","type":"education","lineage":["https://openalex.org/I135310074"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Benjamin Recht","raw_affiliation_strings":["Department of Electrical and Computer Sciences, University of California at Berkeley, Berkeley, CA, USA","University of Wisconsin\u2014Madison, Madison, WI, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Sciences, University of California at Berkeley, Berkeley, CA, USA","institution_ids":["https://openalex.org/I95457486"]},{"raw_affiliation_string":"University of Wisconsin\u2014Madison, Madison, WI, USA","institution_ids":["https://openalex.org/I135310074"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101848896"],"corresponding_institution_ids":["https://openalex.org/I135310074","https://openalex.org/I167576493"],"apc_list":null,"apc_paid":null,"fwci":23.818,"has_fulltext":false,"cited_by_count":181,"citation_normalized_percentile":{"value":0.99843686,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"61","issue":"1","first_page":"499","last_page":"512"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9997000098228455,"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"}},"topics":[{"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/T10534","display_name":"Structural Health Monitoring Techniques","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural Engineering"},"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/semidefinite-programming","display_name":"Semidefinite programming","score":0.8507696390151978},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.8063853979110718},{"id":"https://openalex.org/keywords/minimax","display_name":"Minimax","score":0.8048975467681885},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.554741621017456},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.54117751121521},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.5127657055854797},{"id":"https://openalex.org/keywords/line-search","display_name":"Line search","score":0.5106685757637024},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.5091754794120789},{"id":"https://openalex.org/keywords/upper-and-lower-bounds","display_name":"Upper and lower bounds","score":0.4737442433834076},{"id":"https://openalex.org/keywords/minimax-estimator","display_name":"Minimax estimator","score":0.44726884365081787},{"id":"https://openalex.org/keywords/word-error-rate","display_name":"Word error rate","score":0.4311593770980835},{"id":"https://openalex.org/keywords/spectral-density-estimation","display_name":"Spectral density estimation","score":0.410513699054718},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.35103923082351685},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.15174981951713562},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.11897432804107666},{"id":"https://openalex.org/keywords/minimum-variance-unbiased-estimator","display_name":"Minimum-variance unbiased estimator","score":0.08727473020553589}],"concepts":[{"id":"https://openalex.org/C101901036","wikidata":"https://www.wikidata.org/wiki/Q2269096","display_name":"Semidefinite programming","level":2,"score":0.8507696390151978},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.8063853979110718},{"id":"https://openalex.org/C149728462","wikidata":"https://www.wikidata.org/wiki/Q751319","display_name":"Minimax","level":2,"score":0.8048975467681885},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.554741621017456},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.54117751121521},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.5127657055854797},{"id":"https://openalex.org/C85522705","wikidata":"https://www.wikidata.org/wiki/Q3278015","display_name":"Line search","level":3,"score":0.5106685757637024},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5091754794120789},{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.4737442433834076},{"id":"https://openalex.org/C133939421","wikidata":"https://www.wikidata.org/wiki/Q6865379","display_name":"Minimax estimator","level":4,"score":0.44726884365081787},{"id":"https://openalex.org/C40969351","wikidata":"https://www.wikidata.org/wiki/Q3516228","display_name":"Word error rate","level":2,"score":0.4311593770980835},{"id":"https://openalex.org/C30049272","wikidata":"https://www.wikidata.org/wiki/Q6555326","display_name":"Spectral density estimation","level":3,"score":0.410513699054718},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.35103923082351685},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.15174981951713562},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.11897432804107666},{"id":"https://openalex.org/C165646398","wikidata":"https://www.wikidata.org/wiki/Q3755281","display_name":"Minimum-variance unbiased estimator","level":3,"score":0.08727473020553589},{"id":"https://openalex.org/C178635117","wikidata":"https://www.wikidata.org/wiki/Q747499","display_name":"RADIUS","level":2,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C102519508","wikidata":"https://www.wikidata.org/wiki/Q6520159","display_name":"Fourier transform","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tit.2014.2368122","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tit.2014.2368122","pdf_url":null,"source":{"id":"https://openalex.org/S4502562","display_name":"IEEE Transactions on Information Theory","issn_l":"0018-9448","issn":["0018-9448","1557-9654"],"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 Information Theory","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":47,"referenced_works":["https://openalex.org/W210359992","https://openalex.org/W1480579230","https://openalex.org/W1613006380","https://openalex.org/W1967073510","https://openalex.org/W1999913571","https://openalex.org/W2025727209","https://openalex.org/W2028191993","https://openalex.org/W2038026343","https://openalex.org/W2045110278","https://openalex.org/W2045756756","https://openalex.org/W2053372316","https://openalex.org/W2057603175","https://openalex.org/W2080855151","https://openalex.org/W2103519107","https://openalex.org/W2113638573","https://openalex.org/W2115447612","https://openalex.org/W2116581043","https://openalex.org/W2119499160","https://openalex.org/W2122315118","https://openalex.org/W2125680629","https://openalex.org/W2126607811","https://openalex.org/W2128131274","https://openalex.org/W2137198385","https://openalex.org/W2145096794","https://openalex.org/W2149213383","https://openalex.org/W2149454052","https://openalex.org/W2149755721","https://openalex.org/W2154332973","https://openalex.org/W2158537680","https://openalex.org/W2159700154","https://openalex.org/W2163985581","https://openalex.org/W2167077875","https://openalex.org/W2169892604","https://openalex.org/W2537491518","https://openalex.org/W2565293665","https://openalex.org/W2611328865","https://openalex.org/W2950882525","https://openalex.org/W2962898451","https://openalex.org/W2964253263","https://openalex.org/W2964325628","https://openalex.org/W3099718522","https://openalex.org/W3101040439","https://openalex.org/W3101762025","https://openalex.org/W3124617746","https://openalex.org/W3125735862","https://openalex.org/W4292363360","https://openalex.org/W6664826069"],"related_works":["https://openalex.org/W1983756092","https://openalex.org/W2381295697","https://openalex.org/W2385886188","https://openalex.org/W1546266651","https://openalex.org/W2378309693","https://openalex.org/W1788812054","https://openalex.org/W579949368","https://openalex.org/W2092089517","https://openalex.org/W2024507128","https://openalex.org/W4289793162"],"abstract_inverted_index":{"This":[0],"paper":[1],"establishes":[2],"a":[3,9,27,32,56],"nearly":[4,69],"optimal":[5],"algorithm":[6,20],"for":[7],"denoising":[8],"mixture":[10],"of":[11,102,113],"sinusoids":[12],"from":[13],"noisy":[14],"equispaced":[15],"samples.":[16],"We":[17,36,54,105],"derive":[18,55],"our":[19,67,83,107],"by":[21],"viewing":[22],"line":[23],"spectral":[24,125],"estimation":[25,63,74,126],"as":[26,99],"sparse":[28],"recovery":[29],"problem":[30],"with":[31],"continuous,":[33],"infinite":[34],"dictionary.":[35],"show":[37],"how":[38,81],"to":[39,97],"compute":[40],"the":[41,71,86,89,93,100,118],"estimator":[42,84],"via":[43],"semidefinite":[44,119],"programming":[45,120],"and":[46],"provide":[47],"guarantees":[48],"on":[49,61,80],"its":[50],"mean-squared":[51],"error":[52,95],"rate.":[53],"complementary":[57],"minimax":[58],"lower":[59],"bound":[60],"this":[62],"rate,":[64],"demonstrating":[65,116],"that":[66,92,117],"approach":[68,121],"achieves":[70],"best":[72],"possible":[73],"error.":[75],"Furthermore,":[76],"we":[77],"establish":[78],"bounds":[79],"well":[82],"localizes":[85],"frequencies":[87],"in":[88,110],"signal,":[90],"showing":[91],"localization":[94],"tends":[96],"zero":[98],"number":[101],"samples":[103],"grows.":[104],"verify":[106],"theoretical":[108],"results":[109],"an":[111],"array":[112],"numerical":[114],"experiments,":[115],"outperforms":[122],"three":[123],"classical":[124],"techniques.":[127]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":12},{"year":2023,"cited_by_count":13},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":18},{"year":2020,"cited_by_count":15},{"year":2019,"cited_by_count":15},{"year":2018,"cited_by_count":17},{"year":2017,"cited_by_count":21},{"year":2016,"cited_by_count":38},{"year":2015,"cited_by_count":9},{"year":2014,"cited_by_count":6},{"year":2013,"cited_by_count":1}],"updated_date":"2026-04-18T07:56:08.524223","created_date":"2025-10-10T00:00:00"}
