{"id":"https://openalex.org/W2767990547","doi":"https://doi.org/10.1109/icdsp.2017.8096101","title":"Learning graph structure with stationary graph signals via first-order approximation","display_name":"Learning graph structure with stationary graph signals via first-order approximation","publication_year":2017,"publication_date":"2017-08-01","ids":{"openalex":"https://openalex.org/W2767990547","doi":"https://doi.org/10.1109/icdsp.2017.8096101","mag":"2767990547"},"language":"en","primary_location":{"id":"doi:10.1109/icdsp.2017.8096101","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icdsp.2017.8096101","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 22nd International Conference on Digital Signal Processing (DSP)","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/A5025441627","display_name":"Zhaowei Zhu","orcid":"https://orcid.org/0000-0003-3894-5862"},"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":"Zhaowei Zhu","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/A5055905884","display_name":"Shengda Jin","orcid":null},"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":"Shengda Jin","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/A5081511588","display_name":"Xuming Song","orcid":null},"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":"Xuming Song","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/A5038510002","display_name":"Xiliang Luo","orcid":"https://orcid.org/0000-0003-3816-6789"},"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":"Xiliang Luo","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/A5025441627"],"corresponding_institution_ids":["https://openalex.org/I30809798"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.152643,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":93},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9995999932289124,"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":0.9995999932289124,"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":0.9984999895095825,"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"}},{"id":"https://openalex.org/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.9799000024795532,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/voltage-graph","display_name":"Voltage graph","score":0.6136001944541931},{"id":"https://openalex.org/keywords/laplacian-matrix","display_name":"Laplacian matrix","score":0.6051074266433716},{"id":"https://openalex.org/keywords/butterfly-graph","display_name":"Butterfly graph","score":0.5549566745758057},{"id":"https://openalex.org/keywords/integral-graph","display_name":"Integral graph","score":0.5344359874725342},{"id":"https://openalex.org/keywords/null-graph","display_name":"Null graph","score":0.5145872831344604},{"id":"https://openalex.org/keywords/strength-of-a-graph","display_name":"Strength of a graph","score":0.45643746852874756},{"id":"https://openalex.org/keywords/spectral-graph-theory","display_name":"Spectral graph theory","score":0.44077226519584656},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.42835015058517456},{"id":"https://openalex.org/keywords/line-graph","display_name":"Line graph","score":0.4251599907875061},{"id":"https://openalex.org/keywords/graph-bandwidth","display_name":"Graph bandwidth","score":0.4223198890686035},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.40964072942733765},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.35755154490470886},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.3496606945991516},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.32888782024383545}],"concepts":[{"id":"https://openalex.org/C22149727","wikidata":"https://www.wikidata.org/wiki/Q7940747","display_name":"Voltage graph","level":4,"score":0.6136001944541931},{"id":"https://openalex.org/C115178988","wikidata":"https://www.wikidata.org/wiki/Q772067","display_name":"Laplacian matrix","level":3,"score":0.6051074266433716},{"id":"https://openalex.org/C18819970","wikidata":"https://www.wikidata.org/wiki/Q3035340","display_name":"Butterfly graph","level":5,"score":0.5549566745758057},{"id":"https://openalex.org/C204710682","wikidata":"https://www.wikidata.org/wiki/Q3036983","display_name":"Integral graph","level":5,"score":0.5344359874725342},{"id":"https://openalex.org/C17169500","wikidata":"https://www.wikidata.org/wiki/Q3033506","display_name":"Null graph","level":5,"score":0.5145872831344604},{"id":"https://openalex.org/C19332903","wikidata":"https://www.wikidata.org/wiki/Q7623247","display_name":"Strength of a graph","level":5,"score":0.45643746852874756},{"id":"https://openalex.org/C74003402","wikidata":"https://www.wikidata.org/wiki/Q3180727","display_name":"Spectral graph theory","level":5,"score":0.44077226519584656},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.42835015058517456},{"id":"https://openalex.org/C203776342","wikidata":"https://www.wikidata.org/wiki/Q1378376","display_name":"Line graph","level":3,"score":0.4251599907875061},{"id":"https://openalex.org/C134727501","wikidata":"https://www.wikidata.org/wiki/Q5597073","display_name":"Graph bandwidth","level":5,"score":0.4223198890686035},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.40964072942733765},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.35755154490470886},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.3496606945991516},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.32888782024383545}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icdsp.2017.8096101","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icdsp.2017.8096101","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 22nd International Conference on Digital Signal Processing (DSP)","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":19,"referenced_works":["https://openalex.org/W1541479357","https://openalex.org/W1698699930","https://openalex.org/W1937201840","https://openalex.org/W1964724088","https://openalex.org/W2101491865","https://openalex.org/W2235146554","https://openalex.org/W2299462150","https://openalex.org/W2403759887","https://openalex.org/W2404087539","https://openalex.org/W2463327569","https://openalex.org/W2512995182","https://openalex.org/W2959406683","https://openalex.org/W2963818281","https://openalex.org/W2964012239","https://openalex.org/W2964110841","https://openalex.org/W3105622694","https://openalex.org/W4238253035","https://openalex.org/W6689213722","https://openalex.org/W6704098073"],"related_works":["https://openalex.org/W4292450760","https://openalex.org/W3100627703","https://openalex.org/W2276438615","https://openalex.org/W2026223322","https://openalex.org/W2011469528","https://openalex.org/W2018695296","https://openalex.org/W2081239651","https://openalex.org/W2918674009","https://openalex.org/W2352203679","https://openalex.org/W2767990547"],"abstract_inverted_index":{"Estimating":[0],"the":[1,9,31,38,41,52,72,77,81,93,96,102,110,117,124,131,138],"graph":[2,16,19,42,54,57,61,97,118,126],"structure":[3,55,119],"plays":[4],"an":[5],"important":[6],"role":[7],"in":[8,140],"emerging":[10],"field":[11],"of":[12,37,40,71,80,95,113,137],"signal":[13,26,62],"processing":[14],"on":[15,28],"(SPoG).":[17],"A":[18],"acts":[20],"as":[21],"a":[22,25,35,87,141],"filter":[23],"when":[24],"propagates":[27],"it":[29],"with":[30],"frequency":[32,82],"response":[33],"being":[34],"polynomial":[36,78],"eigenvalues":[39,94],"Laplacian":[43],"matrix.":[44],"In":[45],"this":[46,65],"paper,":[47],"we":[48,67,85],"endeavor":[49],"to":[50,75,91],"learn":[51],"underlying":[53],"(a.k.a.":[56],"connectivity)":[58],"from":[59,123],"stationary":[60],"observations.":[63],"To":[64],"end,":[66],"first":[68],"make":[69],"use":[70],"first-order":[73],"approximation":[74],"linearize":[76],"representation":[79],"response.":[83],"Then":[84],"formulate":[86],"convex":[88],"optimization":[89],"problem":[90,103],"recover":[92],"Laplacian.":[98,127],"We":[99],"further":[100],"show":[101],"can":[104,120],"be":[105,121],"efficiently":[106],"solved":[107],"by":[108],"applying":[109],"alternating-direction":[111],"method":[112],"multipliers":[114],"(ADMM).":[115],"Accordingly,":[116],"learned":[122],"reconstructed":[125],"Numerical":[128],"tests":[129],"demonstrate":[130],"proposed":[132],"approach":[133],"offers":[134],"accurate":[135],"estimates":[136],"connections":[139],"graph.":[142]},"counts_by_year":[{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}