{"id":"https://openalex.org/W2991193286","doi":"https://doi.org/10.1109/icassp40776.2020.9054679","title":"Learning Product Graphs from Multidomain Signals","display_name":"Learning Product Graphs from Multidomain Signals","publication_year":2020,"publication_date":"2020-04-09","ids":{"openalex":"https://openalex.org/W2991193286","doi":"https://doi.org/10.1109/icassp40776.2020.9054679","mag":"2991193286"},"language":"en","primary_location":{"id":"doi:10.1109/icassp40776.2020.9054679","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9054679","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1911.07411","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5074382331","display_name":"Sai Kiran Kadambari","orcid":"https://orcid.org/0000-0001-8940-3284"},"institutions":[{"id":"https://openalex.org/I59270414","display_name":"Indian Institute of Science Bangalore","ror":"https://ror.org/04dese585","country_code":"IN","type":"education","lineage":["https://openalex.org/I59270414"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Sai Kiran Kadambari","raw_affiliation_strings":["Indian Institute of Science, Bangalore, India","[Indian Institute Of Science, Bangalore, India]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Indian Institute of Science, Bangalore, India","institution_ids":["https://openalex.org/I59270414"]},{"raw_affiliation_string":"[Indian Institute Of Science, Bangalore, India]","institution_ids":["https://openalex.org/I59270414"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5015585417","display_name":"Sundeep Prabhakar Chepuri","orcid":"https://orcid.org/0000-0002-0429-6588"},"institutions":[{"id":"https://openalex.org/I59270414","display_name":"Indian Institute of Science Bangalore","ror":"https://ror.org/04dese585","country_code":"IN","type":"education","lineage":["https://openalex.org/I59270414"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Sundeep Prabhakar Chepuri","raw_affiliation_strings":["Indian Institute of Science, Bangalore, India","[Indian Institute Of Science, Bangalore, India]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Indian Institute of Science, Bangalore, India","institution_ids":["https://openalex.org/I59270414"]},{"raw_affiliation_string":"[Indian Institute Of Science, Bangalore, India]","institution_ids":["https://openalex.org/I59270414"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I59270414"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"5665","last_page":"5669"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9933000206947327,"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":0.9933000206947327,"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/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9919000267982483,"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/T10211","display_name":"Computational Drug Discovery Methods","score":0.9589999914169312,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/factor-graph","display_name":"Factor graph","score":0.7104878425598145},{"id":"https://openalex.org/keywords/cartesian-product","display_name":"Cartesian product","score":0.6813502311706543},{"id":"https://openalex.org/keywords/graph-product","display_name":"Graph product","score":0.6410744190216064},{"id":"https://openalex.org/keywords/laplacian-matrix","display_name":"Laplacian matrix","score":0.5925252437591553},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5381181836128235},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5149741768836975},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3930739760398865},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.37504884600639343},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3217296600341797},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3124333322048187},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.2710498571395874},{"id":"https://openalex.org/keywords/line-graph","display_name":"Line graph","score":0.24374228715896606},{"id":"https://openalex.org/keywords/1-planar-graph","display_name":"1-planar graph","score":0.22022026777267456}],"concepts":[{"id":"https://openalex.org/C159246509","wikidata":"https://www.wikidata.org/wiki/Q5428725","display_name":"Factor graph","level":3,"score":0.7104878425598145},{"id":"https://openalex.org/C65236422","wikidata":"https://www.wikidata.org/wiki/Q173740","display_name":"Cartesian product","level":2,"score":0.6813502311706543},{"id":"https://openalex.org/C68103157","wikidata":"https://www.wikidata.org/wiki/Q569347","display_name":"Graph product","level":5,"score":0.6410744190216064},{"id":"https://openalex.org/C115178988","wikidata":"https://www.wikidata.org/wiki/Q772067","display_name":"Laplacian matrix","level":3,"score":0.5925252437591553},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5381181836128235},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5149741768836975},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3930739760398865},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.37504884600639343},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3217296600341797},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3124333322048187},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.2710498571395874},{"id":"https://openalex.org/C203776342","wikidata":"https://www.wikidata.org/wiki/Q1378376","display_name":"Line graph","level":3,"score":0.24374228715896606},{"id":"https://openalex.org/C102192266","wikidata":"https://www.wikidata.org/wiki/Q4545823","display_name":"1-planar graph","level":4,"score":0.22022026777267456},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.0}],"mesh":[],"locations_count":6,"locations":[{"id":"doi:10.1109/icassp40776.2020.9054679","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9054679","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},{"id":"pmh:oai:eprints.iisc.ac.in:66771","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4306401429","display_name":"ePrints@IISc (Indian Institute of Science)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I59270414","host_organization_name":"Indian Institute of Science Bangalore","host_organization_lineage":["https://openalex.org/I59270414"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"","raw_type":"Conference Paper"},{"id":"pmh:oai:arXiv.org:1911.07411","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1911.07411","pdf_url":"https://arxiv.org/pdf/1911.07411","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"mag:2991193286","is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/1911.07411","pdf_url":null,"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":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.1911.07411","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1911.07411","pdf_url":null,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"},{"id":"doi:10.17023/q1eb-9x84","is_oa":true,"landing_page_url":"https://doi.org/10.17023/q1eb-9x84","pdf_url":null,"source":{"id":"https://openalex.org/S7407051697","display_name":"IEEE RESOURCE CENTERS","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Audiovisual"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1911.07411","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1911.07411","pdf_url":"https://arxiv.org/pdf/1911.07411","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[{"display_name":"Clean water and sanitation","id":"https://metadata.un.org/sdg/6","score":0.4099999964237213}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2991193286.pdf","grobid_xml":"https://content.openalex.org/works/W2991193286.grobid-xml"},"referenced_works_count":19,"referenced_works":["https://openalex.org/W1530218127","https://openalex.org/W1583318653","https://openalex.org/W1774304772","https://openalex.org/W1990488619","https://openalex.org/W2101491865","https://openalex.org/W2102412823","https://openalex.org/W2108119513","https://openalex.org/W2490805901","https://openalex.org/W2585019672","https://openalex.org/W2615556757","https://openalex.org/W2959406683","https://openalex.org/W2963384510","https://openalex.org/W2964012239","https://openalex.org/W2964171990","https://openalex.org/W4235934856","https://openalex.org/W4239089288","https://openalex.org/W6631990664","https://openalex.org/W6676321539","https://openalex.org/W6689213722"],"related_works":["https://openalex.org/W3016246029","https://openalex.org/W3203218609","https://openalex.org/W3015230325","https://openalex.org/W2962752727","https://openalex.org/W2791138598","https://openalex.org/W2612384513","https://openalex.org/W1544422618","https://openalex.org/W3138963025","https://openalex.org/W2617467128","https://openalex.org/W2885478882","https://openalex.org/W3080247579","https://openalex.org/W1581695321","https://openalex.org/W857766053","https://openalex.org/W2332701672","https://openalex.org/W1597402313","https://openalex.org/W2789121948","https://openalex.org/W2991281977","https://openalex.org/W2018655547","https://openalex.org/W2350653017","https://openalex.org/W2610919036"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,57],"focus":[4],"on":[5,97,109],"learning":[6,40,80],"the":[7,19,37,43,52,60,67,72,98],"underlying":[8,68],"product":[9,20,28,38,69],"graph":[10,21,27,39,45,54],"structure":[11],"from":[12,24],"multidomain":[13],"training":[14,73],"data.":[15],"We":[16,34],"assume":[17,58],"that":[18,59],"is":[22,62,75,104],"formed":[23],"a":[25,87],"Cartesian":[26],"of":[29],"two":[30],"smaller":[31],"factor":[32,44,53,81],"graphs.":[33],"then":[35],"pose":[36],"problem":[41],"as":[42,86,112,114],"Laplacian":[46,55],"matrix":[47],"estimation":[48],"problem.":[49],"To":[50],"estimate":[51],"matrices,":[56],"data":[61,74,111,116],"smooth":[63],"with":[64],"respect":[65],"to":[66,118],"graph.":[70],"When":[71],"noise":[76],"free":[77],"or":[78],"complete,":[79],"graphs":[82],"can":[83],"be":[84],"formulated":[85],"convex":[88],"optimization":[89],"problem,":[90],"which":[91],"has":[92],"an":[93],"explicit":[94],"solution":[95],"based":[96],"water-filling":[99],"algorithm.":[100],"The":[101],"developed":[102],"framework":[103],"illustrated":[105],"using":[106],"numerical":[107],"experiments":[108],"synthetic":[110],"well":[113],"real":[115],"related":[117],"air":[119],"quality":[120],"monitoring":[121],"in":[122],"India.":[123]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}