{"id":"https://openalex.org/W2526371976","doi":"https://doi.org/10.1109/tpami.2016.2613865","title":"Multi-Instance Classification by Max-Margin Training of Cardinality-Based Markov Networks","display_name":"Multi-Instance Classification by Max-Margin Training of Cardinality-Based Markov Networks","publication_year":2016,"publication_date":"2016-09-27","ids":{"openalex":"https://openalex.org/W2526371976","doi":"https://doi.org/10.1109/tpami.2016.2613865","mag":"2526371976","pmid":"https://pubmed.ncbi.nlm.nih.gov/28114057"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2016.2613865","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2016.2613865","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5060135722","display_name":"Hossein Hajimirsadeghi","orcid":null},"institutions":[{"id":"https://openalex.org/I18014758","display_name":"Simon Fraser University","ror":"https://ror.org/0213rcc28","country_code":"CA","type":"education","lineage":["https://openalex.org/I18014758"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Hossein Hajimirsadeghi","raw_affiliation_strings":["School of Computing Science, Simon Fraser University, Burnaby, BC, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computing Science, Simon Fraser University, Burnaby, BC, Canada","institution_ids":["https://openalex.org/I18014758"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5110713539","display_name":"Greg Mori","orcid":null},"institutions":[{"id":"https://openalex.org/I18014758","display_name":"Simon Fraser University","ror":"https://ror.org/0213rcc28","country_code":"CA","type":"education","lineage":["https://openalex.org/I18014758"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Greg Mori","raw_affiliation_strings":["School of Computing Science, Simon Fraser University, Burnaby, BC, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computing Science, Simon Fraser University, Burnaby, BC, Canada","institution_ids":["https://openalex.org/I18014758"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I18014758"],"apc_list":null,"apc_paid":null,"fwci":0.8287,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.80672468,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"39","issue":"9","first_page":"1839","last_page":"1852"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9990000128746033,"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"}},"topics":[{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9990000128746033,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9908000230789185,"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/T11439","display_name":"Video Analysis and Summarization","score":0.9782999753952026,"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/computer-science","display_name":"Computer science","score":0.7163904905319214},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6559184789657593},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6121000051498413},{"id":"https://openalex.org/keywords/multiclass-classification","display_name":"Multiclass classification","score":0.5959147214889526},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.5700868368148804},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5577354431152344},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5559911131858826},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5519053339958191},{"id":"https://openalex.org/keywords/graphical-model","display_name":"Graphical model","score":0.5479346513748169},{"id":"https://openalex.org/keywords/ambiguity","display_name":"Ambiguity","score":0.5413177013397217},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5198624134063721},{"id":"https://openalex.org/keywords/maximum-entropy-markov-model","display_name":"Maximum-entropy Markov model","score":0.49962663650512695},{"id":"https://openalex.org/keywords/cardinality","display_name":"Cardinality (data modeling)","score":0.4637587070465088},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4528910517692566},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.44499245285987854},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.4292447865009308},{"id":"https://openalex.org/keywords/markov-model","display_name":"Markov model","score":0.32151657342910767},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3156335949897766},{"id":"https://openalex.org/keywords/variable-order-markov-model","display_name":"Variable-order Markov model","score":0.2957719564437866},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16967496275901794},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.14293691515922546}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7163904905319214},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6559184789657593},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6121000051498413},{"id":"https://openalex.org/C123860398","wikidata":"https://www.wikidata.org/wiki/Q6934605","display_name":"Multiclass classification","level":3,"score":0.5959147214889526},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.5700868368148804},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5577354431152344},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5559911131858826},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5519053339958191},{"id":"https://openalex.org/C155846161","wikidata":"https://www.wikidata.org/wiki/Q1143367","display_name":"Graphical model","level":2,"score":0.5479346513748169},{"id":"https://openalex.org/C2780522230","wikidata":"https://www.wikidata.org/wiki/Q1140419","display_name":"Ambiguity","level":2,"score":0.5413177013397217},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5198624134063721},{"id":"https://openalex.org/C196956702","wikidata":"https://www.wikidata.org/wiki/Q6795829","display_name":"Maximum-entropy Markov model","level":5,"score":0.49962663650512695},{"id":"https://openalex.org/C87117476","wikidata":"https://www.wikidata.org/wiki/Q362383","display_name":"Cardinality (data modeling)","level":2,"score":0.4637587070465088},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4528910517692566},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.44499245285987854},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.4292447865009308},{"id":"https://openalex.org/C163836022","wikidata":"https://www.wikidata.org/wiki/Q6771326","display_name":"Markov model","level":3,"score":0.32151657342910767},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3156335949897766},{"id":"https://openalex.org/C54907487","wikidata":"https://www.wikidata.org/wiki/Q7915688","display_name":"Variable-order Markov model","level":4,"score":0.2957719564437866},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16967496275901794},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.14293691515922546},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tpami.2016.2613865","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2016.2613865","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},{"id":"pmid:28114057","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/28114057","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on pattern analysis and machine intelligence","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7300000190734863,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":79,"referenced_works":["https://openalex.org/W53551796","https://openalex.org/W100367037","https://openalex.org/W101414327","https://openalex.org/W172675048","https://openalex.org/W1531742118","https://openalex.org/W1535599202","https://openalex.org/W1562849413","https://openalex.org/W1564684449","https://openalex.org/W1590386482","https://openalex.org/W1607038179","https://openalex.org/W1639006268","https://openalex.org/W1695673519","https://openalex.org/W1799934103","https://openalex.org/W1876515821","https://openalex.org/W2010792435","https://openalex.org/W2011085767","https://openalex.org/W2020934501","https://openalex.org/W2047499569","https://openalex.org/W2053619738","https://openalex.org/W2078579128","https://openalex.org/W2079914085","https://openalex.org/W2098166271","https://openalex.org/W2098239572","https://openalex.org/W2098986246","https://openalex.org/W2103495670","https://openalex.org/W2106848050","https://openalex.org/W2107228074","https://openalex.org/W2108745803","https://openalex.org/W2109235804","https://openalex.org/W2110119381","https://openalex.org/W2113295315","https://openalex.org/W2118253129","https://openalex.org/W2120665803","https://openalex.org/W2125479168","https://openalex.org/W2128981757","https://openalex.org/W2132851637","https://openalex.org/W2133288557","https://openalex.org/W2136595724","https://openalex.org/W2137880010","https://openalex.org/W2141376824","https://openalex.org/W2142863987","https://openalex.org/W2153635508","https://openalex.org/W2154318594","https://openalex.org/W2163474322","https://openalex.org/W2163811596","https://openalex.org/W2166010828","https://openalex.org/W2168356304","https://openalex.org/W2171544105","https://openalex.org/W2171837816","https://openalex.org/W2295144701","https://openalex.org/W2407981807","https://openalex.org/W2962771908","https://openalex.org/W2963210465","https://openalex.org/W2963891219","https://openalex.org/W6604004975","https://openalex.org/W6604120161","https://openalex.org/W6607164772","https://openalex.org/W6631578466","https://openalex.org/W6632825225","https://openalex.org/W6633632867","https://openalex.org/W6635120088","https://openalex.org/W6636455955","https://openalex.org/W6636881423","https://openalex.org/W6637327878","https://openalex.org/W6638190906","https://openalex.org/W6639316738","https://openalex.org/W6664172992","https://openalex.org/W6669992580","https://openalex.org/W6675326130","https://openalex.org/W6676245398","https://openalex.org/W6676909469","https://openalex.org/W6678093388","https://openalex.org/W6679146226","https://openalex.org/W6679492716","https://openalex.org/W6680240620","https://openalex.org/W6684158799","https://openalex.org/W6684348295","https://openalex.org/W6685197027","https://openalex.org/W6697012980"],"related_works":["https://openalex.org/W2352877170","https://openalex.org/W2579577568","https://openalex.org/W2129946993","https://openalex.org/W2963058055","https://openalex.org/W2810755783","https://openalex.org/W2511279186","https://openalex.org/W2276303159","https://openalex.org/W1695673519","https://openalex.org/W2963396445","https://openalex.org/W2526371976"],"abstract_inverted_index":{"We":[0,103],"propose":[1],"a":[2,31,85],"probabilistic":[3],"graphical":[4],"framework":[5,15,66,110],"for":[6,71],"multi-instance":[7,51,99],"learning":[8,89],"(MIL)":[9],"based":[10],"on":[11,111],"Markov":[12,100],"networks.":[13],"This":[14],"can":[16,44,67,145],"deal":[17],"with":[18],"different":[19,49],"levels":[20],"of":[21,27,107,141],"labeling":[22],"ambiguity":[23,142],"(i.e.,":[24],"the":[25,55,97,105,108,139],"portion":[26],"positive":[28],"instances":[29],"in":[30,33,143],"bag)":[32],"weakly":[34],"supervised":[35],"data":[36,144],"by":[37],"parameterizing":[38],"cardinality":[39],"potential":[40],"functions.":[41],"Consequently,":[42],"it":[43],"be":[45,68],"used":[46,70],"to":[47,59,93],"encode":[48],"cardinality-based":[50],"assumptions,":[52],"ranging":[53],"from":[54],"standard":[56],"MIL":[57,115],"assumption":[58],"more":[60],"general":[61],"assumptions.":[62],"In":[63],"addition,":[64],"this":[65,78],"efficiently":[69],"both":[72],"binary":[73,112],"and":[74,84,95,113,129],"multiclass":[75],"classification.":[76],"To":[77],"end,":[79],"an":[80],"efficient":[81],"inference":[82],"algorithm":[83,90],"discriminative":[86],"latent":[87],"max-margin":[88],"are":[91],"introduced":[92],"train":[94],"test":[96],"proposed":[98,109],"network":[101],"models.":[102],"evaluate":[104],"performance":[106],"multi-class":[114],"benchmark":[116],"datasets":[117],"as":[118,120],"well":[119],"two":[121],"challenging":[122],"computer":[123],"vision":[124],"tasks:":[125],"cyclist":[126],"helmet":[127],"recognition":[128],"human":[130],"group":[131],"activity":[132],"recognition.":[133],"Experimental":[134],"results":[135],"verify":[136],"that":[137],"encoding":[138],"degree":[140],"improve":[146],"classification":[147],"performance.":[148]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
