{"id":"https://openalex.org/W3197736921","doi":"https://doi.org/10.1109/isit45174.2021.9517728","title":"Information Theoretic Limits of Exact Recovery in Sub-hypergraph Models for Community Detection","display_name":"Information Theoretic Limits of Exact Recovery in Sub-hypergraph Models for Community Detection","publication_year":2021,"publication_date":"2021-07-12","ids":{"openalex":"https://openalex.org/W3197736921","doi":"https://doi.org/10.1109/isit45174.2021.9517728","mag":"3197736921"},"language":"en","primary_location":{"id":"doi:10.1109/isit45174.2021.9517728","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit45174.2021.9517728","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Symposium on Information Theory (ISIT)","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/A5087332790","display_name":"Jiaiun Liang","orcid":null},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Jiaiun Liang","raw_affiliation_strings":["Purdue University,Department of Statistics,West Lafayette,IN,USA,47907","Department of Statistics, Purdue University, West Lafayette, IN, USA"],"affiliations":[{"raw_affiliation_string":"Purdue University,Department of Statistics,West Lafayette,IN,USA,47907","institution_ids":["https://openalex.org/I219193219"]},{"raw_affiliation_string":"Department of Statistics, Purdue University, West Lafayette, IN, USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024357359","display_name":"Chuyang Ke","orcid":null},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chuyang Ke","raw_affiliation_strings":["Purdue University,Department of Computer Science,West Lafayette,IN,USA,47907","Department of Computer Science, Purdue University, West Lafayette, IN, USA"],"affiliations":[{"raw_affiliation_string":"Purdue University,Department of Computer Science,West Lafayette,IN,USA,47907","institution_ids":["https://openalex.org/I219193219"]},{"raw_affiliation_string":"Department of Computer Science, Purdue University, West Lafayette, IN, USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038965118","display_name":"Jean Honorio","orcid":"https://orcid.org/0000-0002-6448-0598"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jean Honorio","raw_affiliation_strings":["Purdue University,Department of Computer Science,West Lafayette,IN,USA,47907","Department of Computer Science, Purdue University, West Lafayette, IN, USA"],"affiliations":[{"raw_affiliation_string":"Purdue University,Department of Computer Science,West Lafayette,IN,USA,47907","institution_ids":["https://openalex.org/I219193219"]},{"raw_affiliation_string":"Department of Computer Science, Purdue University, West Lafayette, IN, USA","institution_ids":["https://openalex.org/I219193219"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5087332790"],"corresponding_institution_ids":["https://openalex.org/I219193219"],"apc_list":null,"apc_paid":null,"fwci":0.5261,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.65010362,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"2578","last_page":"2583"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9977999925613403,"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"}},"topics":[{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9977999925613403,"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":0.978600025177002,"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/T11106","display_name":"Data Management and Algorithms","score":0.9771999716758728,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/hypergraph","display_name":"Hypergraph","score":0.8654218912124634},{"id":"https://openalex.org/keywords/stochastic-block-model","display_name":"Stochastic block model","score":0.8354491591453552},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.49806690216064453},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4683484435081482},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4570172131061554},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.38896068930625916},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.3726128935813904},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3669853210449219},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.34620362520217896},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.24080613255500793},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.09030613303184509}],"concepts":[{"id":"https://openalex.org/C2781221856","wikidata":"https://www.wikidata.org/wiki/Q840247","display_name":"Hypergraph","level":2,"score":0.8654218912124634},{"id":"https://openalex.org/C2779982251","wikidata":"https://www.wikidata.org/wiki/Q25053762","display_name":"Stochastic block model","level":3,"score":0.8354491591453552},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.49806690216064453},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4683484435081482},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4570172131061554},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.38896068930625916},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.3726128935813904},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3669853210449219},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.34620362520217896},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.24080613255500793},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.09030613303184509}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isit45174.2021.9517728","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit45174.2021.9517728","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Symposium on Information Theory (ISIT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.46000000834465027}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W31172611","https://openalex.org/W1538452572","https://openalex.org/W2012496484","https://openalex.org/W2097777089","https://openalex.org/W2120901716","https://openalex.org/W2470861207","https://openalex.org/W2478708596","https://openalex.org/W2559839022","https://openalex.org/W2602671714","https://openalex.org/W2738793433","https://openalex.org/W2744363584","https://openalex.org/W2798352738","https://openalex.org/W2803224311","https://openalex.org/W2844556331","https://openalex.org/W2884413680","https://openalex.org/W2900800369","https://openalex.org/W2949006289","https://openalex.org/W3035922345","https://openalex.org/W3107391176","https://openalex.org/W4287591375","https://openalex.org/W4287754284","https://openalex.org/W6601272425","https://openalex.org/W6735855921","https://openalex.org/W6750547051","https://openalex.org/W6752969257","https://openalex.org/W6780181083","https://openalex.org/W6786480760"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W4376608589","https://openalex.org/W1537073411","https://openalex.org/W3138003926","https://openalex.org/W3128249290","https://openalex.org/W3137238582","https://openalex.org/W3160515686","https://openalex.org/W3205521290","https://openalex.org/W4224330563","https://openalex.org/W4386230924"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,40],"study":[4],"the":[5,24,35,46,58,68,81,102,111,117,123],"information":[6],"theoretic":[7],"bounds":[8,87],"for":[9,15],"exact":[10],"recovery":[11],"in":[12,106],"sub-hypergraph":[13,29,120],"models":[14,108],"community":[16,103],"detection.":[17],"We":[18,65],"define":[19],"a":[20,62,71,92],"general":[21],"model":[22,32,49],"called":[23],"<tex":[25,36,94],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[26,37,95],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$m$</tex>":[27,38],"-uniform":[28],"stochastic":[30,114],"block":[31,115],"(m-ShSBM).":[33],"Under":[34],"-ShSBM,":[39],"use":[41],"Fano's":[42],"inequality":[43],"to":[44,55,78,91,101],"identify":[45,67],"region":[47,69],"of":[48],"parameters":[50],"where":[51,70],"any":[52],"algorithm":[53,76],"fails":[54],"exactly":[56,79],"recover":[57,80],"planted":[59,112,118,124],"communities":[60,82],"with":[61,83],"large":[63],"probability.":[64,85],"also":[66],"Maximum":[72],"Likelihood":[73],"Estimation":[74],"(MLE)":[75],"succeeds":[77],"high":[84],"Our":[86],"are":[88],"tight":[89],"up":[90],"log(":[93],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$k$</tex>":[96],")":[97],"term":[98],"and":[99,122],"pertain":[100],"detection":[104],"problems":[105],"various":[107],"such":[109],"as":[110],"hypergraph":[113,126],"model,":[116,121],"densest":[119],"multipartite":[125],"model.":[127]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-03-25T13:04:00.132906","created_date":"2025-10-10T00:00:00"}
