{"id":"https://openalex.org/W2996788836","doi":"https://doi.org/10.1145/3336191.3371815","title":"Sampling Subgraphs with Guaranteed Treewidth for Accurate and Efficient Graphical Inference","display_name":"Sampling Subgraphs with Guaranteed Treewidth for Accurate and Efficient Graphical Inference","publication_year":2020,"publication_date":"2020-01-20","ids":{"openalex":"https://openalex.org/W2996788836","doi":"https://doi.org/10.1145/3336191.3371815","mag":"2996788836"},"language":"en","primary_location":{"id":"doi:10.1145/3336191.3371815","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3336191.3371815","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 13th 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/A5036321139","display_name":"Jaemin Yoo","orcid":"https://orcid.org/0000-0001-7237-5117"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Jaemin Yoo","raw_affiliation_strings":["Seoul National University, Seoul, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Seoul National University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074561505","display_name":"U Kang","orcid":"https://orcid.org/0000-0002-8774-6950"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"U Kang","raw_affiliation_strings":["Seoul National University, Seoul, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Seoul National University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058863847","display_name":"Mauro Scanagatta","orcid":"https://orcid.org/0000-0003-4460-591X"},"institutions":[{"id":"https://openalex.org/I2277624104","display_name":"Fondazione Bruno Kessler","ror":"https://ror.org/01j33xk10","country_code":"IT","type":"facility","lineage":["https://openalex.org/I2277624104"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Mauro Scanagatta","raw_affiliation_strings":["Fondazione Bruno Kessler, Trento, Italy"],"affiliations":[{"raw_affiliation_string":"Fondazione Bruno Kessler, Trento, Italy","institution_ids":["https://openalex.org/I2277624104"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047125862","display_name":"Giorgio Corani","orcid":"https://orcid.org/0000-0002-1541-8384"},"institutions":[{"id":"https://openalex.org/I2614128279","display_name":"Dalle Molle Institute for Artificial Intelligence Research","ror":"https://ror.org/013355g38","country_code":"CH","type":"facility","lineage":["https://openalex.org/I15196421","https://openalex.org/I2614128279","https://openalex.org/I57201433"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Giorgio Corani","raw_affiliation_strings":["IDSIA (Istituto Dalle Molle di Studi sull'Intelligenza Artificiale), Lugano, Switzerland"],"affiliations":[{"raw_affiliation_string":"IDSIA (Istituto Dalle Molle di Studi sull'Intelligenza Artificiale), Lugano, Switzerland","institution_ids":["https://openalex.org/I2614128279"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007403791","display_name":"Marco Zaffalon","orcid":"https://orcid.org/0000-0001-8908-1502"},"institutions":[{"id":"https://openalex.org/I2614128279","display_name":"Dalle Molle Institute for Artificial Intelligence Research","ror":"https://ror.org/013355g38","country_code":"CH","type":"facility","lineage":["https://openalex.org/I15196421","https://openalex.org/I2614128279","https://openalex.org/I57201433"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Marco Zaffalon","raw_affiliation_strings":["IDSIA (Istituto Dalle Molle di Studi sull'Intelligenza Artificiale), Lugano, Switzerland"],"affiliations":[{"raw_affiliation_string":"IDSIA (Istituto Dalle Molle di Studi sull'Intelligenza Artificiale), Lugano, Switzerland","institution_ids":["https://openalex.org/I2614128279"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5036321139"],"corresponding_institution_ids":["https://openalex.org/I139264467"],"apc_list":null,"apc_paid":null,"fwci":0.5302,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.7121922,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9976000189781189,"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":0.9976000189781189,"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":0.9973000288009644,"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":0.9854000210762024,"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/graphical-model","display_name":"Graphical model","score":0.8062803745269775},{"id":"https://openalex.org/keywords/treewidth","display_name":"Treewidth","score":0.8035440444946289},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.7777590751647949},{"id":"https://openalex.org/keywords/bounded-function","display_name":"Bounded function","score":0.5677797794342041},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5281146764755249},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5127792954444885},{"id":"https://openalex.org/keywords/tree-decomposition","display_name":"Tree decomposition","score":0.5041550397872925},{"id":"https://openalex.org/keywords/variable-elimination","display_name":"Variable elimination","score":0.47273150086402893},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4496845602989197},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.44439664483070374},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.4319063723087311},{"id":"https://openalex.org/keywords/belief-propagation","display_name":"Belief propagation","score":0.4207385778427124},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.374897301197052},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.29999205470085144},{"id":"https://openalex.org/keywords/pathwidth","display_name":"Pathwidth","score":0.15820229053497314},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.12277626991271973},{"id":"https://openalex.org/keywords/line-graph","display_name":"Line graph","score":0.07480219006538391}],"concepts":[{"id":"https://openalex.org/C155846161","wikidata":"https://www.wikidata.org/wiki/Q1143367","display_name":"Graphical model","level":2,"score":0.8062803745269775},{"id":"https://openalex.org/C132569581","wikidata":"https://www.wikidata.org/wiki/Q5067368","display_name":"Treewidth","level":5,"score":0.8035440444946289},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.7777590751647949},{"id":"https://openalex.org/C34388435","wikidata":"https://www.wikidata.org/wiki/Q2267362","display_name":"Bounded function","level":2,"score":0.5677797794342041},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5281146764755249},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5127792954444885},{"id":"https://openalex.org/C70501317","wikidata":"https://www.wikidata.org/wiki/Q462095","display_name":"Tree decomposition","level":5,"score":0.5041550397872925},{"id":"https://openalex.org/C169272836","wikidata":"https://www.wikidata.org/wiki/Q5668307","display_name":"Variable elimination","level":3,"score":0.47273150086402893},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4496845602989197},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.44439664483070374},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4319063723087311},{"id":"https://openalex.org/C152948882","wikidata":"https://www.wikidata.org/wiki/Q4060686","display_name":"Belief propagation","level":3,"score":0.4207385778427124},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.374897301197052},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.29999205470085144},{"id":"https://openalex.org/C43517604","wikidata":"https://www.wikidata.org/wiki/Q7144893","display_name":"Pathwidth","level":4,"score":0.15820229053497314},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.12277626991271973},{"id":"https://openalex.org/C203776342","wikidata":"https://www.wikidata.org/wiki/Q1378376","display_name":"Line graph","level":3,"score":0.07480219006538391},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3336191.3371815","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3336191.3371815","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 13th International Conference on Web Search and Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W67486310","https://openalex.org/W1511986666","https://openalex.org/W1549390321","https://openalex.org/W1558755690","https://openalex.org/W1565079331","https://openalex.org/W1891202952","https://openalex.org/W2019599312","https://openalex.org/W2037774459","https://openalex.org/W2054358802","https://openalex.org/W2073518383","https://openalex.org/W2077233202","https://openalex.org/W2085550081","https://openalex.org/W2088762494","https://openalex.org/W2103799649","https://openalex.org/W2111708605","https://openalex.org/W2112765151","https://openalex.org/W2116793595","https://openalex.org/W2127931346","https://openalex.org/W2133212379","https://openalex.org/W2146008005","https://openalex.org/W2148123869","https://openalex.org/W2152284345","https://openalex.org/W2153959628","https://openalex.org/W2160450239","https://openalex.org/W2162150749","https://openalex.org/W2163364417","https://openalex.org/W2166128942","https://openalex.org/W2380769351","https://openalex.org/W2539413804","https://openalex.org/W2551340641","https://openalex.org/W2554164694","https://openalex.org/W2556787926","https://openalex.org/W2565403053","https://openalex.org/W2604498196","https://openalex.org/W2774468482","https://openalex.org/W2783128093","https://openalex.org/W2786220088","https://openalex.org/W2951863020","https://openalex.org/W2963316155","https://openalex.org/W2964071773"],"related_works":["https://openalex.org/W959529772","https://openalex.org/W1836127928","https://openalex.org/W4297812452","https://openalex.org/W1576158606","https://openalex.org/W943012151","https://openalex.org/W1490290385","https://openalex.org/W3180766726","https://openalex.org/W2258776623","https://openalex.org/W2955135267","https://openalex.org/W2952683300"],"abstract_inverted_index":{"How":[0],"can":[1,126],"we":[2,35,99],"run":[3,115],"graphical":[4,18,21],"inference":[5,22,54,131,148],"on":[6,103,120],"large":[7],"graphs":[8],"efficiently":[9],"and":[10,20,42,51,106,145,164],"accurately?":[11],"Many":[12],"real-world":[13],"networks":[14],"are":[15],"modeled":[16],"as":[17,85,88],"models,":[19],"is":[23,64,113],"fundamental":[24],"to":[25,114,138,150],"understand":[26],"the":[27,56,60,67,93,110,121,141,169],"properties":[28,94],"of":[29,59,95],"those":[30],"networks.":[31],"In":[32],"this":[33],"work,":[34],"propose":[36],"a":[37,48,77],"novel":[38,73],"approach":[39,102,125],"for":[40],"fast":[41],"accurate":[43],"inference,":[44],"which":[45,112],"first":[46,91],"samples":[47],"small":[49],"subgraph":[50,57,78],"then":[52],"runs":[53],"over":[55],"instead":[58],"given":[61],"graph.":[62,123],"This":[63],"done":[65],"by":[66],"bounded":[68,81],"treewidth":[69,82],"(BTW)":[70],"sampling,":[71],"our":[72,101],"algorithm":[74],"that":[75,166],"generates":[76],"with":[79,109,129,140,153,159],"guaranteed":[80],"while":[83],"retaining":[84],"many":[86],"edges":[87],"possible.":[89],"We":[90,155],"analyze":[92],"BTW":[96,158],"theoretically.":[97],"Then,":[98],"evaluate":[100],"node":[104],"classification":[105],"compare":[107,157],"it":[108,133,167],"baseline":[111],"loopy":[116],"belief":[117],"propagation":[118],"(LBP)":[119],"original":[122],"Our":[124],"be":[127],"coupled":[128],"various":[130],"algorithms:":[132],"shows":[134],"higher":[135],"accuracy":[136],"up":[137,149],"13.7%":[139],"junction":[142],"tree":[143],"algorithm,":[144],"allows":[146],"faster":[147],"23.8":[151],"times":[152],"LBP.":[154],"further":[156],"previous":[160],"graph":[161],"sampling":[162],"algorithms":[163],"show":[165],"gives":[168],"best":[170],"accuracy.":[171]},"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":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}