{"id":"https://openalex.org/W2897013370","doi":"https://doi.org/10.1109/allerton.2018.8635939","title":"Probabilistic Clustering using Maximal Matrix Norm Couplings","display_name":"Probabilistic Clustering using Maximal Matrix Norm Couplings","publication_year":2018,"publication_date":"2018-10-01","ids":{"openalex":"https://openalex.org/W2897013370","doi":"https://doi.org/10.1109/allerton.2018.8635939","mag":"2897013370"},"language":"en","primary_location":{"id":"doi:10.1109/allerton.2018.8635939","is_oa":false,"landing_page_url":"https://doi.org/10.1109/allerton.2018.8635939","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 56th Annual Allerton Conference on Communication, Control, and Computing (Allerton)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://hdl.handle.net/1721.1/137715.2","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5079902855","display_name":"David Qiu","orcid":null},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"David Qiu","raw_affiliation_strings":["EECS Department, Massachusetts Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"EECS Department, Massachusetts Institute of Technology","institution_ids":["https://openalex.org/I63966007"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073197040","display_name":"Anuran Makur","orcid":"https://orcid.org/0000-0002-2978-8116"},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Anuran Makur","raw_affiliation_strings":["EECS Department, Massachusetts Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"EECS Department, Massachusetts Institute of Technology","institution_ids":["https://openalex.org/I63966007"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5112425882","display_name":"Lizhong Zheng","orcid":"https://orcid.org/0000-0002-6108-0222"},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lizhong Zheng","raw_affiliation_strings":["EECS Department, Massachusetts Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"EECS Department, Massachusetts Institute of Technology","institution_ids":["https://openalex.org/I63966007"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I63966007"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"supplement","issue":null,"first_page":"1020","last_page":"1027"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9995999932289124,"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":0.9995999932289124,"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/T10057","display_name":"Face and Expression Recognition","score":0.9991999864578247,"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"}},{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9990000128746033,"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/movielens","display_name":"MovieLens","score":0.7090398073196411},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6650131940841675},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.6161642670631409},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.5723943710327148},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5155494213104248},{"id":"https://openalex.org/keywords/maximization","display_name":"Maximization","score":0.4901743531227112},{"id":"https://openalex.org/keywords/convex-optimization","display_name":"Convex optimization","score":0.47797390818595886},{"id":"https://openalex.org/keywords/random-variable","display_name":"Random variable","score":0.47774308919906616},{"id":"https://openalex.org/keywords/entropy-maximization","display_name":"Entropy maximization","score":0.4488999843597412},{"id":"https://openalex.org/keywords/matrix-norm","display_name":"Matrix norm","score":0.43920162320137024},{"id":"https://openalex.org/keywords/regular-polygon","display_name":"Regular polygon","score":0.43379101157188416},{"id":"https://openalex.org/keywords/norm","display_name":"Norm (philosophy)","score":0.4260375499725342},{"id":"https://openalex.org/keywords/optimization-problem","display_name":"Optimization problem","score":0.4109989106655121},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4085553288459778},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4081876277923584},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.3365152180194855},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.23732173442840576},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.13296666741371155},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.11757421493530273},{"id":"https://openalex.org/keywords/principle-of-maximum-entropy","display_name":"Principle of maximum entropy","score":0.1136433482170105},{"id":"https://openalex.org/keywords/collaborative-filtering","display_name":"Collaborative filtering","score":0.10022342205047607}],"concepts":[{"id":"https://openalex.org/C2776156558","wikidata":"https://www.wikidata.org/wiki/Q4353746","display_name":"MovieLens","level":4,"score":0.7090398073196411},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6650131940841675},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.6161642670631409},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5723943710327148},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5155494213104248},{"id":"https://openalex.org/C2776330181","wikidata":"https://www.wikidata.org/wiki/Q18358244","display_name":"Maximization","level":2,"score":0.4901743531227112},{"id":"https://openalex.org/C157972887","wikidata":"https://www.wikidata.org/wiki/Q463359","display_name":"Convex optimization","level":3,"score":0.47797390818595886},{"id":"https://openalex.org/C122123141","wikidata":"https://www.wikidata.org/wiki/Q176623","display_name":"Random variable","level":2,"score":0.47774308919906616},{"id":"https://openalex.org/C127233936","wikidata":"https://www.wikidata.org/wiki/Q1417473","display_name":"Entropy maximization","level":3,"score":0.4488999843597412},{"id":"https://openalex.org/C92207270","wikidata":"https://www.wikidata.org/wiki/Q939253","display_name":"Matrix norm","level":3,"score":0.43920162320137024},{"id":"https://openalex.org/C112680207","wikidata":"https://www.wikidata.org/wiki/Q714886","display_name":"Regular polygon","level":2,"score":0.43379101157188416},{"id":"https://openalex.org/C191795146","wikidata":"https://www.wikidata.org/wiki/Q3878446","display_name":"Norm (philosophy)","level":2,"score":0.4260375499725342},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.4109989106655121},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4085553288459778},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4081876277923584},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.3365152180194855},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.23732173442840576},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.13296666741371155},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.11757421493530273},{"id":"https://openalex.org/C9679016","wikidata":"https://www.wikidata.org/wiki/Q1417473","display_name":"Principle of maximum entropy","level":2,"score":0.1136433482170105},{"id":"https://openalex.org/C21569690","wikidata":"https://www.wikidata.org/wiki/Q94702","display_name":"Collaborative filtering","level":3,"score":0.10022342205047607},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/allerton.2018.8635939","is_oa":false,"landing_page_url":"https://doi.org/10.1109/allerton.2018.8635939","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 56th Annual Allerton Conference on Communication, Control, and Computing (Allerton)","raw_type":"proceedings-article"},{"id":"pmh:oai:dspace.mit.edu:1721.1/137715.2","is_oa":true,"landing_page_url":"https://hdl.handle.net/1721.1/137715.2","pdf_url":null,"source":{"id":"https://openalex.org/S4306400425","display_name":"DSpace@MIT (Massachusetts Institute of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I63966007","host_organization_name":"Massachusetts Institute of Technology","host_organization_lineage":["https://openalex.org/I63966007"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv","raw_type":"http://purl.org/eprint/type/ConferencePaper"}],"best_oa_location":{"id":"pmh:oai:dspace.mit.edu:1721.1/137715.2","is_oa":true,"landing_page_url":"https://hdl.handle.net/1721.1/137715.2","pdf_url":null,"source":{"id":"https://openalex.org/S4306400425","display_name":"DSpace@MIT (Massachusetts Institute of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I63966007","host_organization_name":"Massachusetts Institute of Technology","host_organization_lineage":["https://openalex.org/I63966007"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv","raw_type":"http://purl.org/eprint/type/ConferencePaper"},"sustainable_development_goals":[{"score":0.550000011920929,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W1488435683","https://openalex.org/W1517289518","https://openalex.org/W1614298861","https://openalex.org/W1686946872","https://openalex.org/W1975406009","https://openalex.org/W1978259121","https://openalex.org/W1995246641","https://openalex.org/W2018582985","https://openalex.org/W2019855902","https://openalex.org/W2022029673","https://openalex.org/W2030748132","https://openalex.org/W2031494345","https://openalex.org/W2039103602","https://openalex.org/W2068848123","https://openalex.org/W2109808436","https://openalex.org/W2124059530","https://openalex.org/W2125031621","https://openalex.org/W2137245235","https://openalex.org/W2150593711","https://openalex.org/W2156718197","https://openalex.org/W2165874743","https://openalex.org/W2250508463","https://openalex.org/W2250539671","https://openalex.org/W2471517265","https://openalex.org/W2478708596","https://openalex.org/W2556383977","https://openalex.org/W2615961873","https://openalex.org/W2742980034","https://openalex.org/W2751449619","https://openalex.org/W2751557834","https://openalex.org/W2950577311","https://openalex.org/W2979454998","https://openalex.org/W3193262203","https://openalex.org/W4213367101","https://openalex.org/W4248624814","https://openalex.org/W4255387915","https://openalex.org/W6630714204","https://openalex.org/W6636510571","https://openalex.org/W6637108112","https://openalex.org/W6678623799","https://openalex.org/W6678885109","https://openalex.org/W6682755970","https://openalex.org/W6684578312","https://openalex.org/W6743484365","https://openalex.org/W6743496057","https://openalex.org/W7070499600"],"related_works":["https://openalex.org/W3102188974","https://openalex.org/W4287870705","https://openalex.org/W3004810941","https://openalex.org/W4297193174","https://openalex.org/W2576492542","https://openalex.org/W1952656308","https://openalex.org/W2267645079","https://openalex.org/W2137556923","https://openalex.org/W2144260821","https://openalex.org/W4295110715"],"abstract_inverted_index":{"In":[0,37],"this":[1,42],"paper,":[2],"we":[3,45],"present":[4],"a":[5,16,23],"local":[6],"information":[7],"theoretic":[8],"approach":[9,73],"to":[10,32,39],"explicitly":[11],"learn":[12],"probabilistic":[13],"clustering":[14],"of":[15,81],"discrete":[17],"random":[18],"variable.":[19],"Our":[20],"formulation":[21],"yields":[22],"convex":[24],"maximization":[25],"problem":[26],"for":[27],"which":[28],"it":[29],"is":[30,74],"NP-hard":[31],"find":[33],"the":[34,60],"global":[35],"optimum.":[36],"order":[38],"algorithmically":[40],"solve":[41],"optimization":[43],"problem,":[44],"propose":[46],"two":[47],"relaxations":[48],"that":[49,71],"are":[50],"solved":[51],"via":[52],"gradient":[53],"ascent":[54],"and":[55,67,79],"alternating":[56],"maximization.":[57],"Experiments":[58],"on":[59],"MSR":[61],"Sentence":[62],"Completion":[63],"Challenge,":[64],"MovieLens":[65],"100K,":[66],"Reuters21578":[68],"datasets":[69],"demonstrate":[70],"our":[72],"competitive":[75],"with":[76],"existing":[77],"techniques":[78],"worthy":[80],"further":[82],"investigation.":[83]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
