{"id":"https://openalex.org/W2938404777","doi":"https://doi.org/10.1109/vtcfall.2018.8690953","title":"Generalized Low-Rank Matrix Completion via Nonconvex Schatten $p$-Norm Minimization","display_name":"Generalized Low-Rank Matrix Completion via Nonconvex Schatten $p$-Norm Minimization","publication_year":2018,"publication_date":"2018-08-01","ids":{"openalex":"https://openalex.org/W2938404777","doi":"https://doi.org/10.1109/vtcfall.2018.8690953","mag":"2938404777"},"language":"en","primary_location":{"id":"doi:10.1109/vtcfall.2018.8690953","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vtcfall.2018.8690953","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 88th Vehicular Technology Conference (VTC-Fall)","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/A5101612845","display_name":"Qiong Wu","orcid":"https://orcid.org/0000-0002-1563-1169"},"institutions":[{"id":"https://openalex.org/I30809798","display_name":"ShanghaiTech University","ror":"https://ror.org/030bhh786","country_code":"CN","type":"education","lineage":["https://openalex.org/I30809798"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qiong Wu","raw_affiliation_strings":["School of Information Science and Technology, ShanghaiTech University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, ShanghaiTech University, Shanghai, China","institution_ids":["https://openalex.org/I30809798"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100403428","display_name":"Fan Zhang","orcid":"https://orcid.org/0000-0002-0343-3499"},"institutions":[{"id":"https://openalex.org/I30809798","display_name":"ShanghaiTech University","ror":"https://ror.org/030bhh786","country_code":"CN","type":"education","lineage":["https://openalex.org/I30809798"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fan Zhang","raw_affiliation_strings":["School of Information Science and Technology, ShanghaiTech University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, ShanghaiTech University, Shanghai, China","institution_ids":["https://openalex.org/I30809798"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042566252","display_name":"Hao Wang","orcid":"https://orcid.org/0000-0001-8821-7260"},"institutions":[{"id":"https://openalex.org/I30809798","display_name":"ShanghaiTech University","ror":"https://ror.org/030bhh786","country_code":"CN","type":"education","lineage":["https://openalex.org/I30809798"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Wang","raw_affiliation_strings":["School of Information Science and Technology, ShanghaiTech University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, ShanghaiTech University, Shanghai, China","institution_ids":["https://openalex.org/I30809798"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022499594","display_name":"Yuanming Shi","orcid":"https://orcid.org/0000-0002-1418-7465"},"institutions":[{"id":"https://openalex.org/I30809798","display_name":"ShanghaiTech University","ror":"https://ror.org/030bhh786","country_code":"CN","type":"education","lineage":["https://openalex.org/I30809798"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanming Shi","raw_affiliation_strings":["School of Information Science and Technology, ShanghaiTech University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, ShanghaiTech University, Shanghai, China","institution_ids":["https://openalex.org/I30809798"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101612845"],"corresponding_institution_ids":["https://openalex.org/I30809798"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.21575397,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"13","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":1.0,"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":1.0,"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/T10931","display_name":"Direction-of-Arrival Estimation Techniques","score":0.9890999794006348,"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"}},{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.983299970626831,"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-completion","display_name":"Matrix completion","score":0.7663663625717163},{"id":"https://openalex.org/keywords/matrix-norm","display_name":"Matrix norm","score":0.7163044214248657},{"id":"https://openalex.org/keywords/low-rank-approximation","display_name":"Low-rank approximation","score":0.7130016684532166},{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.6851922869682312},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.6580787301063538},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.6321938633918762},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5954762697219849},{"id":"https://openalex.org/keywords/iteratively-reweighted-least-squares","display_name":"Iteratively reweighted least squares","score":0.5571783185005188},{"id":"https://openalex.org/keywords/norm","display_name":"Norm (philosophy)","score":0.5186478495597839},{"id":"https://openalex.org/keywords/relaxation","display_name":"Relaxation (psychology)","score":0.4966467022895813},{"id":"https://openalex.org/keywords/minification","display_name":"Minification","score":0.4641370177268982},{"id":"https://openalex.org/keywords/convex-function","display_name":"Convex function","score":0.451206773519516},{"id":"https://openalex.org/keywords/singular-value","display_name":"Singular value","score":0.42266637086868286},{"id":"https://openalex.org/keywords/regular-polygon","display_name":"Regular polygon","score":0.40257376432418823},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3749466836452484},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3380447030067444},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.33754125237464905},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.16797301173210144},{"id":"https://openalex.org/keywords/estimation-theory","display_name":"Estimation theory","score":0.13668647408485413},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.12619340419769287},{"id":"https://openalex.org/keywords/non-linear-least-squares","display_name":"Non-linear least squares","score":0.10159716010093689}],"concepts":[{"id":"https://openalex.org/C2778459887","wikidata":"https://www.wikidata.org/wiki/Q6787865","display_name":"Matrix completion","level":3,"score":0.7663663625717163},{"id":"https://openalex.org/C92207270","wikidata":"https://www.wikidata.org/wiki/Q939253","display_name":"Matrix norm","level":3,"score":0.7163044214248657},{"id":"https://openalex.org/C90199385","wikidata":"https://www.wikidata.org/wiki/Q6692777","display_name":"Low-rank approximation","level":3,"score":0.7130016684532166},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.6851922869682312},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.6580787301063538},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.6321938633918762},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5954762697219849},{"id":"https://openalex.org/C126090379","wikidata":"https://www.wikidata.org/wiki/Q6094424","display_name":"Iteratively reweighted least squares","level":4,"score":0.5571783185005188},{"id":"https://openalex.org/C191795146","wikidata":"https://www.wikidata.org/wiki/Q3878446","display_name":"Norm (philosophy)","level":2,"score":0.5186478495597839},{"id":"https://openalex.org/C2776029896","wikidata":"https://www.wikidata.org/wiki/Q3935810","display_name":"Relaxation (psychology)","level":2,"score":0.4966467022895813},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.4641370177268982},{"id":"https://openalex.org/C145446738","wikidata":"https://www.wikidata.org/wiki/Q319913","display_name":"Convex function","level":3,"score":0.451206773519516},{"id":"https://openalex.org/C109282560","wikidata":"https://www.wikidata.org/wiki/Q4166054","display_name":"Singular value","level":3,"score":0.42266637086868286},{"id":"https://openalex.org/C112680207","wikidata":"https://www.wikidata.org/wiki/Q714886","display_name":"Regular polygon","level":2,"score":0.40257376432418823},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3749466836452484},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3380447030067444},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.33754125237464905},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.16797301173210144},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.13668647408485413},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.12619340419769287},{"id":"https://openalex.org/C45923927","wikidata":"https://www.wikidata.org/wiki/Q3319230","display_name":"Non-linear least squares","level":3,"score":0.10159716010093689},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C25023664","wikidata":"https://www.wikidata.org/wiki/Q1575637","display_name":"Hankel matrix","level":2,"score":0.0},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/vtcfall.2018.8690953","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vtcfall.2018.8690953","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 88th Vehicular Technology Conference (VTC-Fall)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/1","display_name":"No poverty","score":0.4399999976158142}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W195665135","https://openalex.org/W1966060873","https://openalex.org/W1979408141","https://openalex.org/W2004544971","https://openalex.org/W2106005123","https://openalex.org/W2114748345","https://openalex.org/W2136912397","https://openalex.org/W2310614892","https://openalex.org/W2611328865","https://openalex.org/W2963714933","https://openalex.org/W2964170835","https://openalex.org/W2964266674","https://openalex.org/W6607912541","https://openalex.org/W6680391196"],"related_works":["https://openalex.org/W2964006653","https://openalex.org/W2788826952","https://openalex.org/W2084983808","https://openalex.org/W1991825408","https://openalex.org/W4318564253","https://openalex.org/W4302315572","https://openalex.org/W1969698720","https://openalex.org/W1507830821","https://openalex.org/W2184500224","https://openalex.org/W2938404777"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3],"present":[4],"a":[5,78,90],"generalized":[6,53],"low-rank":[7,44,54,185],"matrix":[8],"completion":[9],"(LRMC)":[10],"model":[11],"for":[12,93,167],"topological":[13],"interference":[14],"management":[15],"(TIM),":[16],"thereby":[17],"maximizing":[18],"the":[19,28,48,52,63,84,94,104,122,125,130,140,148,168,177,180],"achievable":[20],"degrees":[21],"of":[22,124,135,179],"freedom":[23],"(DoFs)":[24],"only":[25],"based":[26],"on":[27],"network":[29],"connectivity":[30],"information.":[31],"Unfortunately,":[32],"contemporary":[33],"convex":[34],"relaxation":[35,81],"approaches,":[36,59],"e.g,":[37],"nuclear":[38],"norm":[39,133],"minimization,":[40],"fail":[41],"to":[42,47,88,102,120,143,183],"return":[43],"solutions,":[45,186],"due":[46],"poor":[49],"structures":[50],"in":[51,72,171,194],"model.":[55],"Most":[56],"existing":[57],"nonconvex":[58,80,85,107],"however,":[60],"often":[61],"need":[62],"optimal":[64],"rank":[65,95],"as":[66],"prior":[67],"information,":[68],"which":[69,127,161],"is":[70,100,118],"unavailable":[71],"our":[73],"setting.":[74],"We":[75,145],"thus":[76],"propose":[77],"novel":[79],"approach":[82],"with":[83],"Schatten":[86],"p-norm":[87],"provide":[89],"tight":[91],"approximation":[92],"function.":[96],"A":[97],"smooth":[98],"function":[99],"formulated":[101],"approximate":[103],"nonsmooth":[105],"and":[106],"objective,":[108],"then":[109],"an":[110,152,163],"Iteratively":[111,153],"Reweighted":[112,155],"Least":[113,156],"Squares":[114,157],"(IRLS-":[115],"p)":[116,159],"method":[117],"employed":[119],"handle":[121],"nonconvexity":[123],"model,":[126],"iteratively":[128],"minimizes":[129],"weighted":[131],"Frobenius":[132],"models":[134],"smoothed":[136],"subproblems":[137],"while":[138],"driving":[139],"smoothing":[141,169],"parameter":[142],"0.":[144],"further":[146],"improve":[147],"efficiency":[149],"by":[150],"proposing":[151],"Adaptively":[154],"(IARLS-":[158],"algorithm,":[160],"uses":[162],"adaptively":[164],"updating":[165],"strategy":[166],"parameters":[170],"each":[172],"iteration.":[173],"Numerical":[174],"results":[175],"exhibit":[176],"ability":[178],"proposed":[181],"algorithm":[182],"find":[184],"that":[187],"is,":[188],"it":[189],"can":[190],"achieve":[191],"higher":[192],"DoFs":[193],"most":[195],"cases.":[196]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}