{"id":"https://openalex.org/W1984818422","doi":"https://doi.org/10.1109/mlsp.2015.7324354","title":"Simultaneous instance annotation and clustering in multi-instance multi-label learning","display_name":"Simultaneous instance annotation and clustering in multi-instance multi-label learning","publication_year":2015,"publication_date":"2015-09-01","ids":{"openalex":"https://openalex.org/W1984818422","doi":"https://doi.org/10.1109/mlsp.2015.7324354","mag":"1984818422"},"language":"en","primary_location":{"id":"doi:10.1109/mlsp.2015.7324354","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mlsp.2015.7324354","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE 25th International Workshop on Machine Learning for Signal Processing (MLSP)","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/A5101588169","display_name":"Anh T. Pham","orcid":"https://orcid.org/0000-0003-3898-2727"},"institutions":[{"id":"https://openalex.org/I131249849","display_name":"Oregon State University","ror":"https://ror.org/00ysfqy60","country_code":"US","type":"education","lineage":["https://openalex.org/I131249849"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Anh T. Pham","raw_affiliation_strings":["School of EECS, Oregon State University, Corvallis, OR","School of EECS, Oregon State University, Corvallis, OR, 97331-5501"],"affiliations":[{"raw_affiliation_string":"School of EECS, Oregon State University, Corvallis, OR","institution_ids":["https://openalex.org/I131249849"]},{"raw_affiliation_string":"School of EECS, Oregon State University, Corvallis, OR, 97331-5501","institution_ids":["https://openalex.org/I131249849"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008398853","display_name":"Raviv Raich","orcid":"https://orcid.org/0000-0001-9711-5709"},"institutions":[{"id":"https://openalex.org/I131249849","display_name":"Oregon State University","ror":"https://ror.org/00ysfqy60","country_code":"US","type":"education","lineage":["https://openalex.org/I131249849"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Raviv Raich","raw_affiliation_strings":["School of EECS, Oregon State University, Corvallis, OR","School of EECS, Oregon State University, Corvallis, OR, 97331-5501"],"affiliations":[{"raw_affiliation_string":"School of EECS, Oregon State University, Corvallis, OR","institution_ids":["https://openalex.org/I131249849"]},{"raw_affiliation_string":"School of EECS, Oregon State University, Corvallis, OR, 97331-5501","institution_ids":["https://openalex.org/I131249849"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064053803","display_name":"Xiaoli Z. Fern","orcid":null},"institutions":[{"id":"https://openalex.org/I131249849","display_name":"Oregon State University","ror":"https://ror.org/00ysfqy60","country_code":"US","type":"education","lineage":["https://openalex.org/I131249849"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaoli Z. Fern","raw_affiliation_strings":["School of EECS, Oregon State University, Corvallis, OR","School of EECS, Oregon State University, Corvallis, OR, 97331-5501"],"affiliations":[{"raw_affiliation_string":"School of EECS, Oregon State University, Corvallis, OR","institution_ids":["https://openalex.org/I131249849"]},{"raw_affiliation_string":"School of EECS, Oregon State University, Corvallis, OR, 97331-5501","institution_ids":["https://openalex.org/I131249849"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101588169"],"corresponding_institution_ids":["https://openalex.org/I131249849"],"apc_list":null,"apc_paid":null,"fwci":1.2943,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.85476234,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9983000159263611,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9983000159263611,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9965000152587891,"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/T11309","display_name":"Music and Audio Processing","score":0.9717000126838684,"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/computer-science","display_name":"Computer science","score":0.7621086835861206},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7428919076919556},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.709514856338501},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6632522344589233},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6603755950927734},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6067788004875183},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5699940919876099},{"id":"https://openalex.org/keywords/ambiguity","display_name":"Ambiguity","score":0.5497449636459351},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.5307170152664185},{"id":"https://openalex.org/keywords/graphical-model","display_name":"Graphical model","score":0.48804059624671936},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.4203950762748718},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.40172770619392395},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.39809152483940125}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7621086835861206},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7428919076919556},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.709514856338501},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6632522344589233},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6603755950927734},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6067788004875183},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5699940919876099},{"id":"https://openalex.org/C2780522230","wikidata":"https://www.wikidata.org/wiki/Q1140419","display_name":"Ambiguity","level":2,"score":0.5497449636459351},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5307170152664185},{"id":"https://openalex.org/C155846161","wikidata":"https://www.wikidata.org/wiki/Q1143367","display_name":"Graphical model","level":2,"score":0.48804059624671936},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4203950762748718},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40172770619392395},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.39809152483940125},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","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":1,"locations":[{"id":"doi:10.1109/mlsp.2015.7324354","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mlsp.2015.7324354","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE 25th International Workshop on Machine Learning for Signal Processing (MLSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5899999737739563,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1504012414","https://openalex.org/W1523738436","https://openalex.org/W1838330068","https://openalex.org/W2011430131","https://openalex.org/W2043812437","https://openalex.org/W2049633694","https://openalex.org/W2107887685","https://openalex.org/W2114144277","https://openalex.org/W2121625657","https://openalex.org/W2132509897","https://openalex.org/W2135533176","https://openalex.org/W2137853299","https://openalex.org/W2137917285","https://openalex.org/W2158681777","https://openalex.org/W2296319761","https://openalex.org/W2503956817","https://openalex.org/W2997519153","https://openalex.org/W4250589301","https://openalex.org/W6630165686","https://openalex.org/W6631340511","https://openalex.org/W6638807358","https://openalex.org/W6676180653","https://openalex.org/W6679506024","https://openalex.org/W6680102115","https://openalex.org/W6680293426","https://openalex.org/W6683235360"],"related_works":["https://openalex.org/W2361861616","https://openalex.org/W2353179089","https://openalex.org/W2263699433","https://openalex.org/W2377979023","https://openalex.org/W2218034408","https://openalex.org/W2392921965","https://openalex.org/W2923538289","https://openalex.org/W2353125546","https://openalex.org/W2776613281","https://openalex.org/W2070797946"],"abstract_inverted_index":{"Multi-instance":[0],"multi-label":[1],"learning":[2,76],"(MIML)":[3],"is":[4,24,35,133],"a":[5,20,62,113],"framework":[6,154],"that":[7,116],"addresses":[8,103],"label":[9,22,64],"ambiguity":[10],"when":[11],"data":[12,46],"contains":[13,17],"bags,":[14],"each":[15,27,66,73,96,123],"bag":[16,21],"instances,":[18],"and":[19,79,109,144],"set":[23],"provided":[25],"for":[26,55,65,98,135],"bag.":[28],"Instance":[29],"annotation":[30,57],"in":[31],"the":[32,36,104,136,149,152],"MIML":[33],"setting":[34],"problem":[37],"of":[38,48,51,106,151],"finding":[39],"an":[40],"instance":[41,56,67],"level":[42],"classifier":[43],"given":[44],"training":[45],"consisting":[47],"labeled":[49],"bags":[50],"instances.":[52],"Current":[53],"approaches":[54],"mainly":[58],"focus":[59],"on":[60,130,139],"identifying":[61],"class":[63,97],"without":[68],"considering":[69],"inner":[70,120],"clusters":[71,121],"within":[72,122],"class.":[74,124],"Simultaneously":[75],"to":[77,91,156],"annotate":[78],"cluster":[80,93],"may":[81],"not":[82],"only":[83],"yield":[84],"better":[85],"model":[86,115],"fit":[87],"but":[88],"also":[89],"help":[90],"discovery":[92],"structure":[94],"inside":[95],"future":[99],"investigation.":[100],"This":[101],"paper":[102],"challenge":[105],"simultaneously":[107],"annotating":[108],"clustering":[110],"by":[111],"proposing":[112],"graphical":[114],"takes":[117],"into":[118],"account":[119],"An":[125],"expectation":[126],"maximization":[127],"inference":[128],"based":[129],"maximum":[131],"likelihood":[132],"proposed":[134,153],"model.":[137],"Results":[138],"bird":[140],"song,":[141],"image":[142],"annotation,":[143],"two":[145],"synthetic":[146],"datasets":[147],"illustrate":[148],"effectiveness":[150],"compared":[155],"current":[157],"state-of-the-art":[158],"approaches.":[159]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2016,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
