{"id":"https://openalex.org/W2034109843","doi":"https://doi.org/10.1109/ciss.2012.6310708","title":"Semisupervised domain adaptation for mixture model based classifiers","display_name":"Semisupervised domain adaptation for mixture model based classifiers","publication_year":2012,"publication_date":"2012-03-01","ids":{"openalex":"https://openalex.org/W2034109843","doi":"https://doi.org/10.1109/ciss.2012.6310708","mag":"2034109843"},"language":"en","primary_location":{"id":"doi:10.1109/ciss.2012.6310708","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ciss.2012.6310708","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 46th Annual Conference on Information Sciences and Systems (CISS)","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/A5005867534","display_name":"Jayaram Raghuram","orcid":null},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jayaram Raghuram","raw_affiliation_strings":["Department of EE, Pennsylvania State University, University Park, PA","Department of EE, Pennsylvania State University, University Park, 16801, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of EE, Pennsylvania State University, University Park, PA","institution_ids":["https://openalex.org/I130769515"]},{"raw_affiliation_string":"Department of EE, Pennsylvania State University, University Park, 16801, USA","institution_ids":["https://openalex.org/I130769515"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101739086","display_name":"David J. Miller","orcid":"https://orcid.org/0000-0001-8848-1643"},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"David J. Miller","raw_affiliation_strings":["Department of EE, Pennsylvania State University, University Park, PA","Department of EE, Pennsylvania State University, University Park, 16801, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of EE, Pennsylvania State University, University Park, PA","institution_ids":["https://openalex.org/I130769515"]},{"raw_affiliation_string":"Department of EE, Pennsylvania State University, University Park, 16801, USA","institution_ids":["https://openalex.org/I130769515"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5063903486","display_name":"George Kesidis","orcid":"https://orcid.org/0000-0001-7947-8127"},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"George Kesidis","raw_affiliation_strings":["Department of EE and CSE, Pennsylvania State University, University Park, PA","[Departments of EE and CSE, Pennsylvania State University, University Park, 16801, USA]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of EE and CSE, Pennsylvania State University, University Park, PA","institution_ids":["https://openalex.org/I130769515"]},{"raw_affiliation_string":"[Departments of EE and CSE, Pennsylvania State University, University Park, 16801, USA]","institution_ids":["https://openalex.org/I130769515"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I130769515"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.09906168,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"29","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11598","display_name":"Internet Traffic Analysis and Secure E-voting","score":0.9993000030517578,"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/T11598","display_name":"Internet Traffic Analysis and Secure E-voting","score":0.9993000030517578,"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.996399998664856,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9473999738693237,"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/computer-science","display_name":"Computer science","score":0.7472032904624939},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.7433621883392334},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.635750412940979},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5392201542854309},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.5282137989997864},{"id":"https://openalex.org/keywords/conditional-probability-distribution","display_name":"Conditional probability distribution","score":0.49024659395217896},{"id":"https://openalex.org/keywords/expectation\u2013maximization-algorithm","display_name":"Expectation\u2013maximization algorithm","score":0.482467919588089},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4559590816497803},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4409913420677185},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.41825342178344727},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.38471734523773193},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.18696704506874084},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16570979356765747},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.14545735716819763}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7472032904624939},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.7433621883392334},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.635750412940979},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5392201542854309},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.5282137989997864},{"id":"https://openalex.org/C43555835","wikidata":"https://www.wikidata.org/wiki/Q2300258","display_name":"Conditional probability distribution","level":2,"score":0.49024659395217896},{"id":"https://openalex.org/C182081679","wikidata":"https://www.wikidata.org/wiki/Q1275153","display_name":"Expectation\u2013maximization algorithm","level":3,"score":0.482467919588089},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4559590816497803},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4409913420677185},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.41825342178344727},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38471734523773193},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.18696704506874084},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16570979356765747},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.14545735716819763},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ciss.2012.6310708","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ciss.2012.6310708","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 46th Annual Conference on Information Sciences and Systems (CISS)","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":22,"referenced_works":["https://openalex.org/W1479807131","https://openalex.org/W1596382552","https://openalex.org/W1614659291","https://openalex.org/W2027664152","https://openalex.org/W2049633694","https://openalex.org/W2096118443","https://openalex.org/W2111362445","https://openalex.org/W2120708938","https://openalex.org/W2121981798","https://openalex.org/W2126367746","https://openalex.org/W2137054688","https://openalex.org/W2137900926","https://openalex.org/W2142301198","https://openalex.org/W2158108973","https://openalex.org/W2159570078","https://openalex.org/W2168175751","https://openalex.org/W2484208911","https://openalex.org/W3150719513","https://openalex.org/W6635376254","https://openalex.org/W6677069268","https://openalex.org/W6679974894","https://openalex.org/W6680989407"],"related_works":["https://openalex.org/W3080655457","https://openalex.org/W2145868540","https://openalex.org/W3166286441","https://openalex.org/W3214142563","https://openalex.org/W3136267388","https://openalex.org/W4287263085","https://openalex.org/W3186065094","https://openalex.org/W3204418343","https://openalex.org/W3093803318","https://openalex.org/W4390401377"],"abstract_inverted_index":{"This":[0,76],"paper":[1],"introduces":[2],"a":[3],"method":[4,54],"for":[5,18,26],"mixture":[6],"model-based":[7],"classifier":[8,51],"domain":[9,39,50,60,73,111,141,150,159],"adaptation,":[10],"wherein":[11],"one":[12,19],"has":[13],"adequate":[14],"labeled":[15,24,109],"training":[16],"data":[17,25,120],"(source)":[20],"domain,":[21,29],"very":[22],"scarce":[23],"another":[27],"(target)":[28],"and":[30,37,124,152],"where":[31,85],"the":[32,35,48,53,56,71,86,90,94,108,139,148],"discrepancy":[33],"between":[34],"source":[36,49,140],"target":[38,59,72,110,149],"class-conditional":[40],"distributions":[41],"is":[42,77,96],"not":[43],"\u201ctoo":[44],"great\u201d.":[45],"Starting":[46],"from":[47,107,121],"parameters,":[52],"maximizes":[55],"likelihood":[57],"of":[58,89,138,155],"data,":[61],"while":[62],"constrained":[63],"to":[64,101,134],"agree":[65],"as":[66,68],"much":[67],"possible":[69],"with":[70],"label":[74],"information.":[75],"achieved":[78],"via":[79],"an":[80,156],"expectation":[81],"maximization":[82],"(EM)":[83],"algorithm,":[84],"joint":[87],"distribution":[88],"latent":[91],"variables":[92],"in":[93,99,130],"E-Step":[95],"parametrically":[97],"constrained,":[98],"order":[100],"ensure":[102],"space-partitioning":[103],"implications":[104],"are":[105],"gleaned":[106],"samples.":[112],"Experiments":[113],"on":[114],"publicly":[115],"available":[116],"Internet":[117],"packet-flow":[118],"traffic":[119],"different":[122],"temporal":[123],"spatial":[125],"domains":[126],"demonstrate":[127],"significant":[128],"gains":[129],"classification":[131],"performance":[132],"compared":[133],"1.":[135],"direct":[136],"porting":[137],"classifier;":[142],"2.":[143],"semisupervised":[144],"learning":[145],"using":[146],"only":[147],"data;":[151],"3.":[153],"extension":[154],"existing":[157],"unsupervised":[158],"adaptation":[160],"method.":[161]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}