{"id":"https://openalex.org/W4315605998","doi":"https://doi.org/10.1109/tsp.2022.3229950","title":"Distributionally Robust Graph Learning From Smooth Signals Under Moment Uncertainty","display_name":"Distributionally Robust Graph Learning From Smooth Signals Under Moment Uncertainty","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4315605998","doi":"https://doi.org/10.1109/tsp.2022.3229950"},"language":"en","primary_location":{"id":"doi:10.1109/tsp.2022.3229950","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2022.3229950","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"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 Processing","raw_type":"journal-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/A5078725373","display_name":"Xiaolu Wang","orcid":"https://orcid.org/0000-0002-5267-3464"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiaolu Wang","raw_affiliation_strings":["Department of Systems Engineering and Engineering Management, The Chinese University of Hong Kong, Hong Kong SAR, China"],"affiliations":[{"raw_affiliation_string":"Department of Systems Engineering and Engineering Management, The Chinese University of Hong Kong, Hong Kong SAR, China","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069327861","display_name":"Yuen-Man Pun","orcid":"https://orcid.org/0000-0002-6196-2022"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633"]},{"id":"https://openalex.org/I118347636","display_name":"Australian National University","ror":"https://ror.org/019wvm592","country_code":"AU","type":"education","lineage":["https://openalex.org/I118347636"]}],"countries":["AU","CN"],"is_corresponding":false,"raw_author_name":"Yuen-Man Pun","raw_affiliation_strings":["CIICADA Lab, School of Engineering, The Australian National University, Canberra, ACT, Australia","Department of Systems Engineering and Engineering Management, Chinese University of Hong Kong, Hong Kong"],"affiliations":[{"raw_affiliation_string":"CIICADA Lab, School of Engineering, The Australian National University, Canberra, ACT, Australia","institution_ids":["https://openalex.org/I118347636"]},{"raw_affiliation_string":"Department of Systems Engineering and Engineering Management, Chinese University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5105881332","display_name":"Anthony Man\u2013Cho So","orcid":"https://orcid.org/0000-0003-2588-7851"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Anthony Man-Cho So","raw_affiliation_strings":["Department of Systems Engineering and Engineering Management, The Chinese University of Hong Kong, Hong Kong SAR, China"],"affiliations":[{"raw_affiliation_string":"Department of Systems Engineering and Engineering Management, The Chinese University of Hong Kong, Hong Kong SAR, China","institution_ids":["https://openalex.org/I177725633"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5078725373"],"corresponding_institution_ids":["https://openalex.org/I177725633"],"apc_list":null,"apc_paid":null,"fwci":0.796,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.77416954,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"70","issue":null,"first_page":"6216","last_page":"6231"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9997000098228455,"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":0.9997000098228455,"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":0.9926999807357788,"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/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9800000190734863,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.5897454023361206},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5636695027351379},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5574251413345337},{"id":"https://openalex.org/keywords/robust-optimization","display_name":"Robust optimization","score":0.5132200717926025},{"id":"https://openalex.org/keywords/optimization-problem","display_name":"Optimization problem","score":0.4647454619407654},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.4646448791027069},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.43934303522109985},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.36773401498794556},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3286030888557434},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.31557345390319824},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.28359341621398926},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.15947264432907104}],"concepts":[{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.5897454023361206},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5636695027351379},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5574251413345337},{"id":"https://openalex.org/C193254401","wikidata":"https://www.wikidata.org/wiki/Q2160088","display_name":"Robust optimization","level":2,"score":0.5132200717926025},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.4647454619407654},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.4646448791027069},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.43934303522109985},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36773401498794556},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3286030888557434},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.31557345390319824},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.28359341621398926},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.15947264432907104},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tsp.2022.3229950","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2022.3229950","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"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 Processing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W1128809682","https://openalex.org/W1497214886","https://openalex.org/W1522498890","https://openalex.org/W1774304772","https://openalex.org/W1967138577","https://openalex.org/W2000222149","https://openalex.org/W2056099894","https://openalex.org/W2100659887","https://openalex.org/W2129732816","https://openalex.org/W2131939929","https://openalex.org/W2132914434","https://openalex.org/W2180180824","https://openalex.org/W2615556757","https://openalex.org/W2796431263","https://openalex.org/W2807074140","https://openalex.org/W2914234208","https://openalex.org/W2937507957","https://openalex.org/W2963322627","https://openalex.org/W2963384510","https://openalex.org/W2964012239","https://openalex.org/W2964110122","https://openalex.org/W2964171990","https://openalex.org/W2969738732","https://openalex.org/W2994097903","https://openalex.org/W2999687012","https://openalex.org/W3015953475","https://openalex.org/W3100282875","https://openalex.org/W3162637917","https://openalex.org/W3163642084","https://openalex.org/W4213009331","https://openalex.org/W6629852587","https://openalex.org/W6680914561","https://openalex.org/W6685061373","https://openalex.org/W6689213722","https://openalex.org/W6728768131","https://openalex.org/W6745312988","https://openalex.org/W6746041257","https://openalex.org/W6759340446","https://openalex.org/W6761781411","https://openalex.org/W6769565402","https://openalex.org/W6785107060","https://openalex.org/W6795548309"],"related_works":["https://openalex.org/W2002696586","https://openalex.org/W2793423758","https://openalex.org/W3149055374","https://openalex.org/W2216231335","https://openalex.org/W2053131036","https://openalex.org/W4386254288","https://openalex.org/W4292572523","https://openalex.org/W2809352861","https://openalex.org/W2056349093","https://openalex.org/W2952007803"],"abstract_inverted_index":{"We":[0,167],"consider":[1],"the":[2,17,28,37,64,70,82,100,126,130,143,154,192],"problem":[3,33],"of":[4,12,19,27,118,219],"learning":[5,59,96,194],"a":[6,9,24,32,60,93,109,115,150,162,170,186],"graph":[7,14,29,61,72,95,110,155,193],"from":[8],"finite":[10],"set":[11],"noisy":[13],"signal":[15,156],"observations,":[16],"goal":[18],"which":[20,63,105],"is":[21,34,73,120],"to":[22,39,75,107,174,226],"find":[23],"smooth":[25,116,163],"representation":[26,117],"signal.":[30],"Such":[31],"motivated":[35],"by":[36],"desire":[38],"infer":[40],"relational":[41],"structure":[42],"in":[43,51,125,191],"large":[44],"datasets":[45],"and":[46,178,203],"has":[47,210],"been":[48],"extensively":[49],"studied":[50],"recent":[52],"years.":[53],"Most":[54],"existing":[55,223],"approaches":[56],"focus":[57],"on":[58,62,99,153,189,200],"observed":[65,127,220],"signals":[66,84,221],"are":[67],"smooth.":[68],"However,":[69],"learned":[71],"prone":[74],"overfitting,":[76],"as":[77],"it":[78],"does":[79],"not":[80,112],"take":[81],"unobserved":[83],"into":[85],"account.":[86],"To":[87],"address":[88],"this":[89,176],"issue,":[90],"we":[91,133,146],"propose":[92],"novel":[94],"model":[97,160,209],"based":[98],"distributionally":[101],"robust":[102,122,214],"optimization":[103,144,165],"methodology,":[104],"aims":[106],"identify":[108],"that":[111,148,207],"only":[113],"provides":[114,185],"but":[119],"also":[121],"against":[123],"uncertainties":[124],"signals.":[128],"On":[129,142],"statistics":[131],"side,":[132,145],"establish":[134,179],"out-of-sample":[135],"performance":[136,215],"guarantees":[137],"for":[138],"our":[139,158,208],"proposed":[140,159],"model.":[141],"show":[147,206],"under":[149],"mild":[151],"assumption":[152],"distribution,":[157],"admits":[161],"non-convex":[164],"formulation.":[166],"then":[168],"develop":[169],"projected":[171],"gradient":[172],"method":[173],"tackle":[175],"formulation":[177,184],"its":[180],"convergence":[181],"guarantees.":[182],"Our":[183],"new":[187],"perspective":[188],"regularization":[190],"setting.":[195],"Moreover,":[196],"extensive":[197],"numerical":[198],"experiments":[199],"both":[201],"synthetic":[202],"real-world":[204],"data":[205],"comparable":[211],"yet":[212],"more":[213],"across":[216],"different":[217],"populations":[218],"than":[222],"models":[224],"according":[225],"various":[227],"metrics.":[228]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2023-01-12T00:00:00"}
