{"id":"https://openalex.org/W2127610506","doi":"https://doi.org/10.1109/isit.2013.6620675","title":"On the difficulty of learning power law graphical models","display_name":"On the difficulty of learning power law graphical models","publication_year":2013,"publication_date":"2013-07-01","ids":{"openalex":"https://openalex.org/W2127610506","doi":"https://doi.org/10.1109/isit.2013.6620675","mag":"2127610506"},"language":"en","primary_location":{"id":"doi:10.1109/isit.2013.6620675","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit.2013.6620675","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Symposium on Information Theory","raw_type":"proceedings-article"},"type":"conference-paper","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/A5003933801","display_name":"Rashish Tandon","orcid":null},"institutions":[{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rashish Tandon","raw_affiliation_strings":["Department of Computer Science, University of Texas, Austin, TX, USA","Department of Computer Science, University of Texas at Austin, Austin, TX, USA#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Texas, Austin, TX, USA","institution_ids":["https://openalex.org/I86519309"]},{"raw_affiliation_string":"Department of Computer Science, University of Texas at Austin, Austin, TX, USA#TAB#","institution_ids":["https://openalex.org/I86519309"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053209283","display_name":"Pradeep Ravikumar","orcid":"https://orcid.org/0000-0001-5635-5765"},"institutions":[{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Pradeep Ravikumar","raw_affiliation_strings":["Department of Computer Science, University of Texas, Austin, TX, USA","Department of Computer Science, University of Texas at Austin, Austin, TX, USA#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Texas, Austin, TX, USA","institution_ids":["https://openalex.org/I86519309"]},{"raw_affiliation_string":"Department of Computer Science, University of Texas at Austin, Austin, TX, USA#TAB#","institution_ids":["https://openalex.org/I86519309"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I86519309"],"apc_list":null,"apc_paid":null,"fwci":1.144,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.79691914,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"2493","last_page":"2497"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9991000294685364,"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/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9991000294685364,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9927999973297119,"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/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9821000099182129,"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/power-law","display_name":"Power law","score":0.49313920736312866},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.48250722885131836},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.47167715430259705},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.4449024796485901},{"id":"https://openalex.org/keywords/graph-theory","display_name":"Graph theory","score":0.41319411993026733},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3489653170108795},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.34384676814079285},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.32761597633361816},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.30995452404022217},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.29694390296936035},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.14575490355491638}],"concepts":[{"id":"https://openalex.org/C87040749","wikidata":"https://www.wikidata.org/wiki/Q428971","display_name":"Power law","level":2,"score":0.49313920736312866},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.48250722885131836},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.47167715430259705},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.4449024796485901},{"id":"https://openalex.org/C88230418","wikidata":"https://www.wikidata.org/wiki/Q131476","display_name":"Graph theory","level":2,"score":0.41319411993026733},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3489653170108795},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.34384676814079285},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.32761597633361816},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.30995452404022217},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.29694390296936035},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.14575490355491638}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isit.2013.6620675","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit.2013.6620675","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Symposium on Information Theory","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7699999809265137,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W135467536","https://openalex.org/W638149299","https://openalex.org/W1735349781","https://openalex.org/W1967440046","https://openalex.org/W1976969221","https://openalex.org/W1982687752","https://openalex.org/W2008620264","https://openalex.org/W2010824638","https://openalex.org/W2060615452","https://openalex.org/W2067247412","https://openalex.org/W2106958800","https://openalex.org/W2107151623","https://openalex.org/W2112090702","https://openalex.org/W2112976607","https://openalex.org/W2127610506","https://openalex.org/W2128208871","https://openalex.org/W2185993773","https://openalex.org/W2997134027","https://openalex.org/W3098834468","https://openalex.org/W3098888484","https://openalex.org/W3142570770","https://openalex.org/W3143219376","https://openalex.org/W6637823461","https://openalex.org/W6676199244","https://openalex.org/W6676225092","https://openalex.org/W6686663181","https://openalex.org/W6793127252"],"related_works":["https://openalex.org/W4287880334","https://openalex.org/W4366700029","https://openalex.org/W4285230481","https://openalex.org/W4385769873","https://openalex.org/W2015759683","https://openalex.org/W4281634296","https://openalex.org/W4319161863","https://openalex.org/W2371687270","https://openalex.org/W4307819175","https://openalex.org/W4311888330"],"abstract_inverted_index":{"A":[0],"power-law":[1,50,82],"graph":[2,5,24,58],"is":[3,29],"any":[4],"G":[6],"=":[7],"(V,":[8],"E),":[9],"whose":[10,56],"degree":[11,26],"distribution":[12],"follows":[13],"a":[14],"power":[15,61],"law":[16],"i.e.":[17,53],"the":[18,23,44,60,72],"number":[19],"of":[20,47,71],"vertices":[21],"in":[22],"with":[25],"i,":[27],"yi,":[28],"proportional":[30],"to":[31],"i-\u03b2:":[32],"yi\u221d":[33],"i-\u03b2.":[34],"In":[35,63],"this":[36],"paper,":[37],"we":[38,65],"provide":[39],"information-theoretic":[40],"lower":[41],"bounds":[42],"on":[43],"sample":[45,79],"complexity":[46,80],"learning":[48],"such":[49],"graphical":[51,54],"models":[52,55],"Markov":[57],"obeys":[59],"law.":[62],"addition,":[64],"briefly":[66],"revisit":[67],"some":[68],"existing":[69],"state":[70],"art":[73],"estimators,":[74],"and":[75],"explicitly":[76],"derive":[77],"their":[78],"for":[81],"graphs.":[83]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":3},{"year":2016,"cited_by_count":1},{"year":2014,"cited_by_count":3},{"year":2013,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
