{"id":"https://openalex.org/W2404959429","doi":"https://doi.org/10.1109/icassp.2016.7472448","title":"Blind identification of graph filters with multiple sparse inputs","display_name":"Blind identification of graph filters with multiple sparse inputs","publication_year":2016,"publication_date":"2016-03-01","ids":{"openalex":"https://openalex.org/W2404959429","doi":"https://doi.org/10.1109/icassp.2016.7472448","mag":"2404959429"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2016.7472448","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2016.7472448","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5012007074","display_name":"Santiago Segarra","orcid":"https://orcid.org/0000-0002-8408-9633"},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Santiago Segarra","raw_affiliation_strings":["Dept. of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, PA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, PA, USA","institution_ids":["https://openalex.org/I79576946"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054312245","display_name":"Antonio G. Marqu\u00e9s","orcid":"https://orcid.org/0000-0002-4642-7718"},"institutions":[{"id":"https://openalex.org/I182083151","display_name":"Universidad Rey Juan Carlos","ror":"https://ror.org/01v5cv687","country_code":"ES","type":"education","lineage":["https://openalex.org/I182083151"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Antonio G. Marques","raw_affiliation_strings":["Dept. of Signal Theory and Communications, King Juan Carlos University, Madrid, Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Signal Theory and Communications, King Juan Carlos University, Madrid, Spain","institution_ids":["https://openalex.org/I182083151"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006078163","display_name":"Gonzalo Mateos","orcid":"https://orcid.org/0000-0002-9847-6298"},"institutions":[{"id":"https://openalex.org/I5388228","display_name":"University of Rochester","ror":"https://ror.org/022kthw22","country_code":"US","type":"education","lineage":["https://openalex.org/I5388228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gonzalo Mateos","raw_affiliation_strings":["Dept. of Electrical and Computer Engineering, University of Rochester, Rochester, NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Electrical and Computer Engineering, University of Rochester, Rochester, NY, USA","institution_ids":["https://openalex.org/I5388228"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5078862959","display_name":"Alejandro Ribeiro","orcid":"https://orcid.org/0000-0003-4230-9906"},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alejandro Ribeiro","raw_affiliation_strings":["Dept. of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, PA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, PA, USA","institution_ids":["https://openalex.org/I79576946"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.5986,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.91698262,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":"100","issue":null,"first_page":"4099","last_page":"4103"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9957000017166138,"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"}},"topics":[{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9957000017166138,"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.9771999716758728,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5680618286132812},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.509484589099884},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4880481958389282},{"id":"https://openalex.org/keywords/blind-deconvolution","display_name":"Blind deconvolution","score":0.47647950053215027},{"id":"https://openalex.org/keywords/signal-processing","display_name":"Signal processing","score":0.43901464343070984},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.4250360131263733},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3647090792655945},{"id":"https://openalex.org/keywords/deconvolution","display_name":"Deconvolution","score":0.33877408504486084},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.28200748562812805}],"concepts":[{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5680618286132812},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.509484589099884},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4880481958389282},{"id":"https://openalex.org/C30044814","wikidata":"https://www.wikidata.org/wiki/Q11334452","display_name":"Blind deconvolution","level":3,"score":0.47647950053215027},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.43901464343070984},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.4250360131263733},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3647090792655945},{"id":"https://openalex.org/C174576160","wikidata":"https://www.wikidata.org/wiki/Q1183700","display_name":"Deconvolution","level":2,"score":0.33877408504486084},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.28200748562812805},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2016.7472448","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2016.7472448","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1526135953","https://openalex.org/W1541479357","https://openalex.org/W1567700673","https://openalex.org/W1684305122","https://openalex.org/W1698699930","https://openalex.org/W1945792210","https://openalex.org/W1966096622","https://openalex.org/W1991252559","https://openalex.org/W2101491865","https://openalex.org/W2107861471","https://openalex.org/W2110355775","https://openalex.org/W2118550318","https://openalex.org/W2119449648","https://openalex.org/W2140867429","https://openalex.org/W2147656689","https://openalex.org/W2154332973","https://openalex.org/W2159929956","https://openalex.org/W2164278908","https://openalex.org/W2213622371","https://openalex.org/W2245913236","https://openalex.org/W2484918290","https://openalex.org/W2486096428","https://openalex.org/W2549164117","https://openalex.org/W3104684837","https://openalex.org/W4292363360","https://openalex.org/W6631441237","https://openalex.org/W6633952271","https://openalex.org/W6640646553"],"related_works":["https://openalex.org/W2059639161","https://openalex.org/W2058895457","https://openalex.org/W1538056422","https://openalex.org/W2586325539","https://openalex.org/W2023738877","https://openalex.org/W2147401053","https://openalex.org/W2589098082","https://openalex.org/W2029084792","https://openalex.org/W2139898842","https://openalex.org/W4321635651"],"abstract_inverted_index":{"Network":[0],"processes":[1],"are":[2],"often":[3],"represented":[4],"as":[5,26,77,190,192],"signals":[6,65,167,198],"defined":[7],"on":[8],"the":[9,16,40,55,67,78,84,89,96,116,126,129,184,187,193,201],"vertices":[10],"of":[11,19,28,42,45,57,61,80,91,112,125,128,186,195],"a":[12,46,72,81,109,122],"graph.":[13],"To":[14],"untangle":[15],"latent":[17],"structure":[18],"such":[20],"signals,":[21],"one":[22],"can":[23,141],"view":[24],"them":[25],"outputs":[27],"linear":[29,123,152],"graph":[30,47,69,73,82,118,137],"filters":[31],"modeling":[32],"underlying":[33],"network":[34],"dynamics.":[35],"This":[36],"paper":[37],"deals":[38],"with":[39,178],"problem":[41,140],"joint":[43],"identification":[44,139,203],"filter":[48,92,138],"and":[49,63,95,114,147,180],"its":[50],"input":[51,97],"signal,":[52],"thus":[53,143],"broadening":[54],"scope":[56],"classical":[58],"blind":[59,136,202],"deconvolution":[60],"temporal":[62],"spatial":[64],"to":[66,87,103,151,157,169,199],"less-structured":[68],"domain.":[70],"Given":[71],"signal":[74,98,119],"y":[75,107],"modeled":[76],"output":[79,166],"filter,":[83],"goal":[85],"is":[86,101,108,120,173],"recover":[88],"vector":[90],"coefficients":[93],"h,":[94,115],"x":[99,113],"which":[100],"assumed":[102],"be":[104,142],"sparse.":[105],"While":[106],"bilinear":[110],"function":[111],"filtered":[117],"also":[121,174],"combination":[124],"entries":[127],"\"lifted\"":[130],"rank-one,":[131],"row-sparse":[132],"matrix":[133],"xhT.":[134],"The":[135],"tackled":[144],"via":[145],"rank":[146],"sparsity":[148],"minimization":[149],"subject":[150],"constraints,":[153],"an":[154],"approach":[155],"amenable":[156],"convex":[158],"relaxation.":[159],"An":[160],"algorithm":[161],"for":[162],"jointly":[163],"processing":[164],"multiple":[165,197],"corresponding":[168],"different":[170],"sparse":[171],"inputs":[172],"developed.":[175],"Numerical":[176],"tests":[177],"synthetic":[179],"real-world":[181],"networks":[182],"illustrate":[183],"merits":[185],"proposed":[188],"algorithm,":[189],"well":[191],"benefits":[194],"leveraging":[196],"aid":[200],"task.":[204]},"counts_by_year":[{"year":2020,"cited_by_count":2},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}