{"id":"https://openalex.org/W3081079206","doi":"https://doi.org/10.1109/tsipn.2021.3059995","title":"Kernel-Based Graph Learning From Smooth Signals: A Functional Viewpoint","display_name":"Kernel-Based Graph Learning From Smooth Signals: A Functional Viewpoint","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3081079206","doi":"https://doi.org/10.1109/tsipn.2021.3059995","mag":"3081079206"},"language":"en","primary_location":{"id":"doi:10.1109/tsipn.2021.3059995","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsipn.2021.3059995","pdf_url":null,"source":{"id":"https://openalex.org/S4306422866","display_name":"IEEE Transactions on Signal and Information Processing over Networks","issn_l":"2373-776X","issn":["2373-776X","2373-7778"],"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 Signal and Information Processing over Networks","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2008.10065","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5068847658","display_name":"Xingyue Pu","orcid":"https://orcid.org/0000-0002-9841-0619"},"institutions":[{"id":"https://openalex.org/I4210146410","display_name":"Science Oxford","ror":"https://ror.org/04j8yhy50","country_code":"GB","type":"nonprofit","lineage":["https://openalex.org/I4210146410"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Xingyue Pu","raw_affiliation_strings":["Oxford-Man Institute, and the Department of Engineering Science, University of Oxford, Oxford, U.K"],"raw_orcid":"https://orcid.org/0000-0002-9841-0619","affiliations":[{"raw_affiliation_string":"Oxford-Man Institute, and the Department of Engineering Science, University of Oxford, Oxford, U.K","institution_ids":["https://openalex.org/I4210146410"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051223998","display_name":"Siu Lun Chau","orcid":null},"institutions":[{"id":"https://openalex.org/I40120149","display_name":"University of Oxford","ror":"https://ror.org/052gg0110","country_code":"GB","type":"education","lineage":["https://openalex.org/I40120149"]},{"id":"https://openalex.org/I4210146410","display_name":"Science Oxford","ror":"https://ror.org/04j8yhy50","country_code":"GB","type":"nonprofit","lineage":["https://openalex.org/I4210146410"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Siu Lun Chau","raw_affiliation_strings":["Department of Statistics, University of Oxford, Oxford, U.K"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics, University of Oxford, Oxford, U.K","institution_ids":["https://openalex.org/I40120149","https://openalex.org/I4210146410"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101579932","display_name":"Xiaowen Dong","orcid":"https://orcid.org/0000-0002-1143-9786"},"institutions":[{"id":"https://openalex.org/I4210146410","display_name":"Science Oxford","ror":"https://ror.org/04j8yhy50","country_code":"GB","type":"nonprofit","lineage":["https://openalex.org/I4210146410"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Xiaowen Dong","raw_affiliation_strings":["Oxford-Man Institute, and the Department of Engineering Science, University of Oxford, Oxford, U.K"],"raw_orcid":"https://orcid.org/0000-0002-1143-9786","affiliations":[{"raw_affiliation_string":"Oxford-Man Institute, and the Department of Engineering Science, University of Oxford, Oxford, U.K","institution_ids":["https://openalex.org/I4210146410"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5040046354","display_name":"Dino Sejdinovi\u0107","orcid":"https://orcid.org/0000-0001-5547-9213"},"institutions":[{"id":"https://openalex.org/I40120149","display_name":"University of Oxford","ror":"https://ror.org/052gg0110","country_code":"GB","type":"education","lineage":["https://openalex.org/I40120149"]},{"id":"https://openalex.org/I4210146410","display_name":"Science Oxford","ror":"https://ror.org/04j8yhy50","country_code":"GB","type":"nonprofit","lineage":["https://openalex.org/I4210146410"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Dino Sejdinovic","raw_affiliation_strings":["Department of Statistics, University of Oxford, Oxford, U.K"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics, University of Oxford, Oxford, U.K","institution_ids":["https://openalex.org/I40120149","https://openalex.org/I4210146410"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.0011,"has_fulltext":false,"cited_by_count":21,"citation_normalized_percentile":{"value":0.8797064,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"7","issue":null,"first_page":"192","last_page":"207"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9998999834060669,"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":0.9998999834060669,"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/T12292","display_name":"Graph Theory and Algorithms","score":0.9980000257492065,"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"}},{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9966999888420105,"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/computer-science","display_name":"Computer science","score":0.5426211357116699},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5345641374588013},{"id":"https://openalex.org/keywords/graph-kernel","display_name":"Graph kernel","score":0.4931427836418152},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.490875780582428},{"id":"https://openalex.org/keywords/polynomial-kernel","display_name":"Polynomial kernel","score":0.46815919876098633},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4509434998035431},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3563779592514038},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3521258533000946},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.30207234621047974},{"id":"https://openalex.org/keywords/kernel-method","display_name":"Kernel method","score":0.2603170871734619},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.16818606853485107},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.1532110869884491}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5426211357116699},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5345641374588013},{"id":"https://openalex.org/C100595998","wikidata":"https://www.wikidata.org/wiki/Q11731931","display_name":"Graph kernel","level":5,"score":0.4931427836418152},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.490875780582428},{"id":"https://openalex.org/C160446489","wikidata":"https://www.wikidata.org/wiki/Q7226642","display_name":"Polynomial kernel","level":4,"score":0.46815919876098633},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4509434998035431},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3563779592514038},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3521258533000946},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.30207234621047974},{"id":"https://openalex.org/C122280245","wikidata":"https://www.wikidata.org/wiki/Q620622","display_name":"Kernel method","level":3,"score":0.2603170871734619},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.16818606853485107},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.1532110869884491}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tsipn.2021.3059995","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsipn.2021.3059995","pdf_url":null,"source":{"id":"https://openalex.org/S4306422866","display_name":"IEEE Transactions on Signal and Information Processing over Networks","issn_l":"2373-776X","issn":["2373-776X","2373-7778"],"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 Signal and Information Processing over Networks","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2008.10065","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2008.10065","pdf_url":"https://arxiv.org/pdf/2008.10065","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"raw_type":"text"},{"id":"pmh:oai:ora.ox.ac.uk:uuid:93c026ee-1e0e-49e9-97ef-7fb3c5599fe7","is_oa":false,"landing_page_url":"https://ora.ox.ac.uk/objects/uuid:93c026ee-1e0e-49e9-97ef-7fb3c5599fe7","pdf_url":null,"source":{"id":"https://openalex.org/S4306402636","display_name":"Oxford University Research Archive (ORA) (University of Oxford)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I40120149","host_organization_name":"University of Oxford","host_organization_lineage":["https://openalex.org/I40120149"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Symplectic Elements","raw_type":"Journal article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2008.10065","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2008.10065","pdf_url":"https://arxiv.org/pdf/2008.10065","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":109,"referenced_works":["https://openalex.org/W1540764732","https://openalex.org/W1627400044","https://openalex.org/W1774304772","https://openalex.org/W1964590153","https://openalex.org/W1991252559","https://openalex.org/W1993273815","https://openalex.org/W2044600950","https://openalex.org/W2078828682","https://openalex.org/W2101491865","https://openalex.org/W2104290444","https://openalex.org/W2105760337","https://openalex.org/W2106351931","https://openalex.org/W2110026675","https://openalex.org/W2116805437","https://openalex.org/W2122825543","https://openalex.org/W2123499997","https://openalex.org/W2131237233","https://openalex.org/W2132555912","https://openalex.org/W2132914434","https://openalex.org/W2133396774","https://openalex.org/W2141566892","https://openalex.org/W2145065594","https://openalex.org/W2151128232","https://openalex.org/W2158170196","https://openalex.org/W2165558283","https://openalex.org/W2252136820","https://openalex.org/W2401715402","https://openalex.org/W2553303224","https://openalex.org/W2558748708","https://openalex.org/W2585019672","https://openalex.org/W2610153490","https://openalex.org/W2615556757","https://openalex.org/W2626958527","https://openalex.org/W2765944436","https://openalex.org/W2782758556","https://openalex.org/W2787337315","https://openalex.org/W2796431263","https://openalex.org/W2796728297","https://openalex.org/W2798585159","https://openalex.org/W2804375450","https://openalex.org/W2887005491","https://openalex.org/W2889900103","https://openalex.org/W2898648503","https://openalex.org/W2907492528","https://openalex.org/W2924719072","https://openalex.org/W2936036845","https://openalex.org/W2946123091","https://openalex.org/W2948729509","https://openalex.org/W2949979136","https://openalex.org/W2952369555","https://openalex.org/W2959406683","https://openalex.org/W2962759781","https://openalex.org/W2962886429","https://openalex.org/W2962886701","https://openalex.org/W2962965968","https://openalex.org/W2963043672","https://openalex.org/W2963089591","https://openalex.org/W2963364599","https://openalex.org/W2963374479","https://openalex.org/W2963384510","https://openalex.org/W2963464736","https://openalex.org/W2963549694","https://openalex.org/W2963702033","https://openalex.org/W2964012239","https://openalex.org/W2964171990","https://openalex.org/W2964277180","https://openalex.org/W2966398094","https://openalex.org/W2969543297","https://openalex.org/W2980288697","https://openalex.org/W2991348544","https://openalex.org/W2994097903","https://openalex.org/W2994821362","https://openalex.org/W2997701990","https://openalex.org/W2999687012","https://openalex.org/W3011667710","https://openalex.org/W3015742334","https://openalex.org/W3028192203","https://openalex.org/W3037401512","https://openalex.org/W3046300977","https://openalex.org/W3080253043","https://openalex.org/W3100282875","https://openalex.org/W3104959188","https://openalex.org/W3111112539","https://openalex.org/W4210257598","https://openalex.org/W4287871935","https://openalex.org/W4289799350","https://openalex.org/W4297825594","https://openalex.org/W4388323202","https://openalex.org/W6636759986","https://openalex.org/W6675747103","https://openalex.org/W6677437772","https://openalex.org/W6679719908","https://openalex.org/W6682227116","https://openalex.org/W6683048519","https://openalex.org/W6689213722","https://openalex.org/W6691476020","https://openalex.org/W6696497002","https://openalex.org/W6729956949","https://openalex.org/W6737558694","https://openalex.org/W6739593606","https://openalex.org/W6746041257","https://openalex.org/W6747800994","https://openalex.org/W6748320467","https://openalex.org/W6754506371","https://openalex.org/W6755965654","https://openalex.org/W6760886919","https://openalex.org/W6766114393","https://openalex.org/W6771263443","https://openalex.org/W6773860202"],"related_works":["https://openalex.org/W3095395190","https://openalex.org/W4389428786","https://openalex.org/W2382515812","https://openalex.org/W3123056048","https://openalex.org/W3100948281","https://openalex.org/W2179275589","https://openalex.org/W1983263273","https://openalex.org/W2974741803","https://openalex.org/W1558903433","https://openalex.org/W2029578388"],"abstract_inverted_index":{"The":[0,118,183],"problem":[1],"of":[2,8,30,39,124],"graph":[3,43,53,78,85,107,112,125,134,164,170,187,199,221,224],"learning":[4,41,54,104,108,120,126,200,218],"concerns":[5],"the":[6,14,28,37,68,74,90,114,122,133,149,159,163,166,186,192,197,214],"construction":[7],"an":[9,23],"explicit":[10],"topological":[11],"structure":[12],"revealing":[13],"relationship":[15,115],"between":[16,116],"nodes":[17],"representing":[18,113],"data":[19,208],"entities,":[20],"which":[21],"plays":[22],"increasingly":[24],"important":[25],"role":[26],"in":[27,36,66,77,89,132,181,217,226],"success":[29],"many":[31],"graph-based":[32,142],"representations":[33],"and":[34,42,62,65,101,129,165,206,233],"algorithms":[35],"field":[38],"machine":[40],"signal":[44],"processing.":[45],"In":[46,136],"this":[47,81],"paper,":[48],"we":[49,83,138],"propose":[50],"a":[51,97,111,140,219],"novel":[52,141],"framework":[55],"that":[56,70,210],"incorporates":[57],"prior":[58],"information":[59,131],"along":[60],"node":[61],"observation":[63],"side,":[64],"particular":[67,227],"covariates":[69],"help":[71],"to":[72,109,156,169],"explain":[73],"dependency":[75,160,167],"structures":[76],"signals.":[79,135],"To":[80],"end,":[82],"consider":[84],"signals":[86,171,188],"as":[87],"functions":[88],"reproducing":[91],"kernel":[92],"Hilbert":[93],"space":[94],"associated":[95],"with":[96,105,148,228],"Kronecker":[98,150],"product":[99,151],"kernel,":[100,152],"integrate":[102],"functional":[103,119],"smoothness-promoting":[106],"learn":[110],"nodes.":[117],"increases":[121],"robustness":[123],"against":[127],"missing":[128,231],"incomplete":[130],"addition,":[137],"develop":[139],"regularisation":[143],"method":[144],"which,":[145],"when":[146],"combined":[147],"enables":[153],"our":[154,211],"model":[155],"capture":[157],"both":[158,204],"explained":[161],"by":[162,196],"due":[168],"observed":[172],"under":[173],"different":[174,179],"but":[175],"related":[176],"circumstances,":[177],"e.g.":[178],"points":[180],"time.":[182],"latter":[184],"means":[185],"are":[189],"free":[190],"from":[191,223],"i.i.d.":[193],"assumptions":[194],"required":[195],"classical":[198],"models.":[201],"Experiments":[202],"on":[203],"synthetic":[205],"real-world":[207],"show":[209],"methods":[212],"outperform":[213],"state-of-the-art":[215],"models":[216],"meaningful":[220],"topology":[222],"signals,":[225],"heavy":[229],"noise,":[230],"values,":[232],"multiple":[234],"dependency.":[235]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":1}],"updated_date":"2026-08-12T21:12:35.861297","created_date":"2025-10-10T00:00:00"}
