{"id":"https://openalex.org/W3118087899","doi":"https://doi.org/10.1145/3437963.3441756","title":"Exploring the Subgraph Density-Size Trade-off via the Lova\u015bz Extension","display_name":"Exploring the Subgraph Density-Size Trade-off via the Lova\u015bz Extension","publication_year":2021,"publication_date":"2021-03-06","ids":{"openalex":"https://openalex.org/W3118087899","doi":"https://doi.org/10.1145/3437963.3441756","mag":"3118087899"},"language":"en","primary_location":{"id":"doi:10.1145/3437963.3441756","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3437963.3441756","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 14th ACM International Conference on Web Search and Data Mining","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/A5011509788","display_name":"Aritra Konar","orcid":"https://orcid.org/0000-0002-9330-0277"},"institutions":[{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Aritra Konar","raw_affiliation_strings":["University of Virginia, Charlottesville, VA, USA"],"affiliations":[{"raw_affiliation_string":"University of Virginia, Charlottesville, VA, USA","institution_ids":["https://openalex.org/I51556381"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050186120","display_name":"Nicholas D. Sidiropoulos","orcid":"https://orcid.org/0000-0002-3385-7911"},"institutions":[{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nicholas D. Sidiropoulos","raw_affiliation_strings":["University of Virginia, Charlottesville, VA, USA"],"affiliations":[{"raw_affiliation_string":"University of Virginia, Charlottesville, VA, USA","institution_ids":["https://openalex.org/I51556381"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5011509788"],"corresponding_institution_ids":["https://openalex.org/I51556381"],"apc_list":null,"apc_paid":null,"fwci":0.8878,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.76601064,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"743","last_page":"751"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10720","display_name":"Complexity and Algorithms in Graphs","score":0.9993000030517578,"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"}},"topics":[{"id":"https://openalex.org/T10720","display_name":"Complexity and Algorithms in Graphs","score":0.9993000030517578,"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"}},{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10374","display_name":"Advanced Graph Theory Research","score":0.9850000143051147,"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/submodular-set-function","display_name":"Submodular set function","score":0.9261016845703125},{"id":"https://openalex.org/keywords/rounding","display_name":"Rounding","score":0.656168520450592},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5079646706581116},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.48431435227394104},{"id":"https://openalex.org/keywords/cardinality","display_name":"Cardinality (data modeling)","score":0.4800873398780823},{"id":"https://openalex.org/keywords/extension","display_name":"Extension (predicate logic)","score":0.4501695930957794},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.44994983077049255},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.41331297159194946},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3516636788845062}],"concepts":[{"id":"https://openalex.org/C178621042","wikidata":"https://www.wikidata.org/wiki/Q7631710","display_name":"Submodular set function","level":2,"score":0.9261016845703125},{"id":"https://openalex.org/C136625980","wikidata":"https://www.wikidata.org/wiki/Q663208","display_name":"Rounding","level":2,"score":0.656168520450592},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5079646706581116},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.48431435227394104},{"id":"https://openalex.org/C87117476","wikidata":"https://www.wikidata.org/wiki/Q362383","display_name":"Cardinality (data modeling)","level":2,"score":0.4800873398780823},{"id":"https://openalex.org/C2778029271","wikidata":"https://www.wikidata.org/wiki/Q5421931","display_name":"Extension (predicate logic)","level":2,"score":0.4501695930957794},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.44994983077049255},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.41331297159194946},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3516636788845062},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3437963.3441756","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3437963.3441756","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 14th ACM International Conference on Web Search and Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5054795683","display_name":null,"funder_award_id":"IIS 1908070","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8718338721","display_name":null,"funder_award_id":"W911NF1910407","funder_id":"https://openalex.org/F4320338281","funder_display_name":"Army Research Office"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320338281","display_name":"Army Research Office","ror":"https://ror.org/05epdh915"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W1502940150","https://openalex.org/W1535144194","https://openalex.org/W1589208139","https://openalex.org/W1974874717","https://openalex.org/W1986080131","https://openalex.org/W1996215314","https://openalex.org/W1998991750","https://openalex.org/W2002559252","https://openalex.org/W2013469283","https://openalex.org/W2019569173","https://openalex.org/W2030365814","https://openalex.org/W2034543148","https://openalex.org/W2036836182","https://openalex.org/W2047923585","https://openalex.org/W2054560566","https://openalex.org/W2065641139","https://openalex.org/W2086058123","https://openalex.org/W2091602684","https://openalex.org/W2136885855","https://openalex.org/W2137404238","https://openalex.org/W2164278908","https://openalex.org/W2266714125","https://openalex.org/W2348679751","https://openalex.org/W2399911911","https://openalex.org/W2482182218","https://openalex.org/W2552383377","https://openalex.org/W2621438471","https://openalex.org/W2951914620","https://openalex.org/W2988480584","https://openalex.org/W3041093287","https://openalex.org/W3141595720","https://openalex.org/W4239425118","https://openalex.org/W4241652050","https://openalex.org/W4286469038"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W1595919516","https://openalex.org/W2945022594","https://openalex.org/W2194604332","https://openalex.org/W4379619607","https://openalex.org/W1989453388","https://openalex.org/W4321600307","https://openalex.org/W4398796424","https://openalex.org/W24519920","https://openalex.org/W2087778462"],"abstract_inverted_index":{"Given":[0],"an":[1,118],"undirected":[2],"graph,":[3],"the":[4,18,21,25,45,57,77,89,96,100,104,108,142,151,189],"Densest-k-Subgraph":[5],"problem":[6,31],"(DkS)":[7],"seeks":[8],"to":[9,34,42,63,72,94,134],"find":[10],"a":[11,52,68,73,83,112,136,156,184],"subset":[12],"of":[13,20,103,111,146,158],"k":[14],"vertices":[15],"such":[16],"that":[17,79,127,165],"sum":[19],"edge":[22],"weights":[23],"in":[24,44,121],"corresponding":[26],"subgraph":[27],"is":[28,32,38,62],"maximized.":[29],"The":[30],"known":[33],"be":[35],"NP-hard,":[36],"and":[37,174],"also":[39],"very":[40],"difficult":[41],"approximate,":[43],"worst-case.":[46],"In":[47],"this":[48,132],"paper,":[49],"we":[50,92,125,163],"present":[51],"new":[53],"convex":[54,101],"relaxation":[55],"for":[56,123,149],"problem.":[58,153],"Our":[59],"key":[60],"idea":[61],"reformulate":[64],"DkS":[65,124],"as":[66,88],"minimizing":[67],"submodular":[69,80,113],"function":[70,114],"subject":[71],"cardinality":[74,105],"constraint.":[75],"Exploiting":[76],"fact":[78],"functions":[81],"possess":[82],"convex,":[84],"continuous":[85],"extension":[86,98,110],"(known":[87],"Lovasz":[90,97,109],"extension),":[91],"propose":[93],"minimize":[95],"over":[99],"hull":[102],"constraints.":[106],"Although":[107],"does":[115],"not":[116],"admit":[117],"analytical":[119],"form":[120],"general,":[122],"show":[126],"it":[128],"does.":[129],"We":[130],"leverage":[131],"result":[133],"develop":[135],"highly":[137],"scalable":[138],"algorithm":[139],"based":[140],"on":[141,171],"Alternating":[143],"Direction":[144],"Method":[145],"Multipliers":[147],"(ADMM)":[148],"solving":[150],"relaxed":[152],"Coupled":[154],"with":[155],"pair":[157],"fortuitously":[159],"simple":[160],"rounding":[161],"schemes,":[162],"demonstrate":[164],"our":[166],"approach":[167],"outperforms":[168],"existing":[169],"baselines":[170],"real-world":[172],"graphs":[173],"can":[175],"yield":[176],"high":[177],"quality":[178],"sub-optimal":[179],"solutions":[180],"which":[181],"typically":[182],"are":[183],"posteriori":[185],"no":[186],"worse":[187],"than65-80%of":[188],"optimal":[190],"density.":[191]},"counts_by_year":[{"year":2024,"cited_by_count":5},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
