{"id":"https://openalex.org/W2008538025","doi":"https://doi.org/10.1109/iros.2013.6696673","title":"Contextual modeling with labeled multi-LDA","display_name":"Contextual modeling with labeled multi-LDA","publication_year":2013,"publication_date":"2013-11-01","ids":{"openalex":"https://openalex.org/W2008538025","doi":"https://doi.org/10.1109/iros.2013.6696673","mag":"2008538025"},"language":"en","primary_location":{"id":"doi:10.1109/iros.2013.6696673","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros.2013.6696673","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE/RSJ International Conference on Intelligent Robots and Systems","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-134127","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100439643","display_name":"Cheng Zhang","orcid":"https://orcid.org/0000-0002-4510-0238"},"institutions":[{"id":"https://openalex.org/I86987016","display_name":"KTH Royal Institute of Technology","ror":"https://ror.org/026vcq606","country_code":"SE","type":"education","lineage":["https://openalex.org/I86987016"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Cheng Zhang","raw_affiliation_strings":["CVAP/CAS, KTH, Stockholm, Sweden","CVAP, KTH, Stockholm, Sweden"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CVAP/CAS, KTH, Stockholm, Sweden","institution_ids":[]},{"raw_affiliation_string":"CVAP, KTH, Stockholm, Sweden","institution_ids":["https://openalex.org/I86987016"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100634207","display_name":"Dan Song","orcid":"https://orcid.org/0000-0002-5864-0276"},"institutions":[{"id":"https://openalex.org/I86987016","display_name":"KTH Royal Institute of Technology","ror":"https://ror.org/026vcq606","country_code":"SE","type":"education","lineage":["https://openalex.org/I86987016"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Dan Song","raw_affiliation_strings":["CVAP/CAS, KTH, Stockholm, Sweden","CVAP, KTH, Stockholm, Sweden"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CVAP/CAS, KTH, Stockholm, Sweden","institution_ids":[]},{"raw_affiliation_string":"CVAP, KTH, Stockholm, Sweden","institution_ids":["https://openalex.org/I86987016"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021003965","display_name":"Hedvig Kjellstr\u00f6m","orcid":"https://orcid.org/0000-0002-5750-9655"},"institutions":[{"id":"https://openalex.org/I86987016","display_name":"KTH Royal Institute of Technology","ror":"https://ror.org/026vcq606","country_code":"SE","type":"education","lineage":["https://openalex.org/I86987016"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Hedvig Kjellstrom","raw_affiliation_strings":["CVAP/CAS, KTH, Stockholm, Sweden","CVAP, KTH, Stockholm, Sweden"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CVAP/CAS, KTH, Stockholm, Sweden","institution_ids":[]},{"raw_affiliation_string":"CVAP, KTH, Stockholm, Sweden","institution_ids":["https://openalex.org/I86987016"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I86987016"],"apc_list":null,"apc_paid":null,"fwci":1.0394,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.79133293,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"2264","last_page":"2271"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":1.0,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":1.0,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","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/T10812","display_name":"Human Pose and Action Recognition","score":0.9993000030517578,"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":0.7721055746078491},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7202624082565308},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6635703444480896},{"id":"https://openalex.org/keywords/affordance","display_name":"Affordance","score":0.6103639006614685},{"id":"https://openalex.org/keywords/latent-dirichlet-allocation","display_name":"Latent Dirichlet allocation","score":0.5987072587013245},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5841442346572876},{"id":"https://openalex.org/keywords/grasp","display_name":"GRASP","score":0.5751734972000122},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.5190273523330688},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.4661238193511963},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.46598002314567566},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.4365941286087036},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.41931864619255066},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4145238697528839},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.4104537069797516},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.15639027953147888},{"id":"https://openalex.org/keywords/topic-model","display_name":"Topic model","score":0.1167336106300354}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7721055746078491},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7202624082565308},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6635703444480896},{"id":"https://openalex.org/C194995250","wikidata":"https://www.wikidata.org/wiki/Q531136","display_name":"Affordance","level":2,"score":0.6103639006614685},{"id":"https://openalex.org/C500882744","wikidata":"https://www.wikidata.org/wiki/Q269236","display_name":"Latent Dirichlet allocation","level":3,"score":0.5987072587013245},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5841442346572876},{"id":"https://openalex.org/C171268870","wikidata":"https://www.wikidata.org/wiki/Q1486676","display_name":"GRASP","level":2,"score":0.5751734972000122},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.5190273523330688},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.4661238193511963},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.46598002314567566},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.4365941286087036},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41931864619255066},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4145238697528839},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.4104537069797516},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.15639027953147888},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.1167336106300354},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/iros.2013.6696673","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros.2013.6696673","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE/RSJ International Conference on Intelligent Robots and Systems","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.588.2173","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.588.2173","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.csc.kth.se/~hedvig/publications/iros_13.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.727.7400","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.727.7400","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.csc.kth.se/%7Echengz/IROS13_1323_FI.pdf","raw_type":"text"},{"id":"pmh:oai:DiVA.org:kth-134127","is_oa":true,"landing_page_url":"http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-134127","pdf_url":null,"source":{"id":"https://openalex.org/S4306401559","display_name":"KTH Publication Database DiVA (KTH Royal Institute of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":{"id":"pmh:oai:DiVA.org:kth-134127","is_oa":true,"landing_page_url":"http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-134127","pdf_url":null,"source":{"id":"https://openalex.org/S4306401559","display_name":"KTH Publication Database DiVA (KTH Royal Institute of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/conferenceObject"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320322581","display_name":"Vetenskapsr\u00e5det","ror":"https://ror.org/03zttf063"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":54,"referenced_works":["https://openalex.org/W1545773936","https://openalex.org/W1612003148","https://openalex.org/W1684361744","https://openalex.org/W1880262756","https://openalex.org/W1966747088","https://openalex.org/W1969486090","https://openalex.org/W1976869522","https://openalex.org/W1998197760","https://openalex.org/W2009761865","https://openalex.org/W2015089916","https://openalex.org/W2020163092","https://openalex.org/W2020842694","https://openalex.org/W2038517147","https://openalex.org/W2040999325","https://openalex.org/W2047197161","https://openalex.org/W2047346158","https://openalex.org/W2082521326","https://openalex.org/W2091797369","https://openalex.org/W2098062695","https://openalex.org/W2098517267","https://openalex.org/W2098782609","https://openalex.org/W2103658758","https://openalex.org/W2107034620","https://openalex.org/W2110591510","https://openalex.org/W2122683976","https://openalex.org/W2129004009","https://openalex.org/W2139117248","https://openalex.org/W2140435402","https://openalex.org/W2141364309","https://openalex.org/W2149035855","https://openalex.org/W2149173366","https://openalex.org/W2151103935","https://openalex.org/W2153690652","https://openalex.org/W2158266063","https://openalex.org/W2159564241","https://openalex.org/W2161050705","https://openalex.org/W2163292664","https://openalex.org/W2165605600","https://openalex.org/W2166761907","https://openalex.org/W2169393274","https://openalex.org/W2950477597","https://openalex.org/W2963208507","https://openalex.org/W4211008118","https://openalex.org/W4237791300","https://openalex.org/W4241200240","https://openalex.org/W4248892431","https://openalex.org/W4252381709","https://openalex.org/W6632709538","https://openalex.org/W6636440780","https://openalex.org/W6675276727","https://openalex.org/W6680382358","https://openalex.org/W6680735884","https://openalex.org/W6684114947","https://openalex.org/W6834357723"],"related_works":["https://openalex.org/W1972718289","https://openalex.org/W1791514435","https://openalex.org/W3014080459","https://openalex.org/W4386875794","https://openalex.org/W2951631158","https://openalex.org/W4288313544","https://openalex.org/W2976611405","https://openalex.org/W4288282832","https://openalex.org/W2956331735","https://openalex.org/W2963244934"],"abstract_inverted_index":{"Learning":[0],"about":[1],"activities":[2],"and":[3,26,68,156,175],"object":[4,132],"affordances":[5],"from":[6,137],"human":[7,17],"demonstration":[8],"are":[9,90,116],"important":[10],"cognitive":[11,164],"capabilities":[12],"for":[13,19,32,59,86,129,153,173],"robots":[14],"functioning":[15],"in":[16,118,163],"environments,":[18],"example,":[20],"being":[21],"able":[22],"to":[23,29,83],"classify":[24],"objects":[25],"knowing":[27],"how":[28],"grasp":[30],"them":[31],"different":[33,56],"tasks.":[34],"To":[35],"achieve":[36],"such":[37],"capabilities,":[38],"we":[39],"propose":[40],"a":[41,50,159,170,176],"Labeled":[42],"Multi-modal":[43],"Latent":[44],"Dirichlet":[45],"Allocation":[46],"(LM-LDA),":[47],"which":[48],"is":[49],"generative":[51],"classifier":[52],"trained":[53],"with":[54,94],"two":[55],"data":[57],"cues,":[58],"instance,":[60],"one":[61,96,122],"cue":[62,70,111,114,140],"can":[63,71,134],"be":[64,72,107,135],"traditional":[65],"visual":[66],"observation":[67],"another":[69],"contextual":[73,88],"information.":[74],"The":[75],"novel":[76],"aspects":[77],"of":[78,97,123,144,179],"the":[79,98,104,119,124,130,138,142,145,150,180],"LM-LDA":[80],"classifier,":[81],"compared":[82],"other":[84,139],"methods":[85],"encoding":[87],"information":[89],"that,":[91],"I)":[92],"even":[93],"only":[95],"cues":[99,125],"present":[100],"at":[101],"execution":[102],"time,":[103],"classification":[105,112,174],"will":[106],"better":[108],"than":[109],"single":[110],"since":[113],"correlations":[115],"encoded":[117],"model,":[120],"II)":[121],"(e.g.,":[126,141],"common":[127],"grasps":[128],"observed":[131,146],"class)":[133],"inferred":[136],"appearance":[143],"object).":[147],"This":[148],"makes":[149],"method":[151],"suitable":[152],"robot":[154],"online":[155],"transfer":[157],"learning;":[158],"capability":[160],"highly":[161],"desirable":[162],"robotic":[165],"applications.":[166],"Our":[167],"experiments":[168],"show":[169],"clear":[171],"improvement":[172],"reasonable":[177],"inference":[178],"missing":[181],"data.":[182]},"counts_by_year":[{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":2},{"year":2013,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}