{"id":"https://openalex.org/W1563100697","doi":null,"title":"Metric Learning for Graph-Based Domain Adaptation","display_name":"Metric Learning for Graph-Based Domain Adaptation","publication_year":2012,"publication_date":"2012-12-01","ids":{"openalex":"https://openalex.org/W1563100697","mag":"1563100697"},"language":"en","primary_location":{"id":"pmh:oai:repository.upenn.edu:cis_reports-2021","doi":null,"is_oa":true,"landing_page_url":"https://repository.upenn.edu/cis_reports/975","pdf_url":"https://repository.upenn.edu/cis_reports/975","source":{"id":"https://openalex.org/S4306402083","display_name":"ScholarlyCommons (University of Pennsylvania)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I79576946","host_organization_name":"University of Pennsylvania","host_organization_lineage":["https://openalex.org/I79576946"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Technical Reports (CIS)","raw_type":"text"},"volume":null,"type":"article","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://repository.upenn.edu/cis_reports/975","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5063223563","display_name":"Paramveer S. Dhillon","orcid":"https://orcid.org/0000-0002-0994-9488","observed_orcids":["https://orcid.org/0000-0002-0994-9488"]},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Paramveer S. Dhillon","raw_affiliation_strings":["#N#               * University of Pennsylvania"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"#N#               * University of Pennsylvania","institution_ids":["https://openalex.org/I79576946"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033696194","display_name":"Partha Pratim Talukdar","orcid":"https://orcid.org/0000-0001-8825-589X","observed_orcids":["https://orcid.org/0000-0001-8825-589X"]},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Partha Talukdar","raw_affiliation_strings":["Carnegie Mellon University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006419939","display_name":"Koby Crammer","orcid":"https://orcid.org/0000-0001-8824-5747","observed_orcids":["https://orcid.org/0000-0001-8824-5747"]},"institutions":[{"id":"https://openalex.org/I174306211","display_name":"Technion \u2013 Israel Institute of Technology","ror":"https://ror.org/03qryx823","country_code":"IL","type":"education","lineage":["https://openalex.org/I174306211"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Koby Crammer","raw_affiliation_strings":["TECHNION-Israel Institute of Technology"],"raw_orcid":"https://orcid.org/0000-0001-8824-5747","affiliations":[{"raw_affiliation_string":"TECHNION-Israel Institute of Technology","institution_ids":["https://openalex.org/I174306211"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2902,"has_fulltext":true,"cited_by_count":7,"citation_normalized_percentile":{"value":0.61289749,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"255","last_page":"264"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":1.0,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":1.0,"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/T12072","display_name":"Machine Learning and Algorithms","score":9.999999747378752e-05,"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":0.0,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"domain adaptation","score":0.8640000224113464},{"id":"https://openalex.org/keywords/metric-learning","display_name":"metric learning","score":0.9829999804496765},{"id":"https://openalex.org/keywords/graph-based-semi-supervised-learning","display_name":"graph-based semi-supervised learning","score":0.9359999895095825},{"id":"https://openalex.org/keywords/similarity-graph","display_name":"similarity graph","score":0.5619999766349792},{"id":"https://openalex.org/keywords/edge-weighting","display_name":"edge weighting","score":0.6079999804496765},{"id":"https://openalex.org/keywords/unlabeled-data","display_name":"unlabeled data","score":0.7480000257492065},{"id":"https://openalex.org/keywords/cross-domain-classification","display_name":"cross-domain classification","score":0.6179999709129333}],"concepts":[{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.6884843707084656},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.6217764019966125},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.5947567820549011},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5811408162117004},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.552500307559967},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5101445317268372},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.48959141969680786},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.46538108587265015},{"id":"https://openalex.org/C58973888","wikidata":"https://www.wikidata.org/wiki/Q1041418","display_name":"Semi-supervised learning","level":2,"score":0.4313724637031555},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4245200753211975},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.4232906401157379},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3531164228916168},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3435574173927307},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32283279299736023},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.12215203046798706},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.0913718044757843},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","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},{"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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":7,"locations":[{"id":"pmh:oai:repository.upenn.edu:cis_reports-2021","doi":null,"is_oa":true,"landing_page_url":"https://repository.upenn.edu/cis_reports/975","pdf_url":"https://repository.upenn.edu/cis_reports/975","source":{"id":"https://openalex.org/S4306402083","display_name":"ScholarlyCommons (University of Pennsylvania)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I79576946","host_organization_name":"University of Pennsylvania","host_organization_lineage":["https://openalex.org/I79576946"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Technical Reports (CIS)","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.248.7641","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.248.7641","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.304.3886","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.304.3886","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.talukdar.net/papers/graph_da_coling12.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.378.8986","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.378.8986","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://aclweb.org/anthology/C/C12/C12-2026.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.381.25","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.381.25","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.seas.upenn.edu/~pasingh/graph_da_coling_2012.pdf","raw_type":"text"},{"id":"pmh:oai:repository.upenn.edu:20.500.14332/7947","doi":null,"is_oa":false,"landing_page_url":"https://repository.upenn.edu/handle/20.500.14332/7947","pdf_url":null,"source":{"id":"https://openalex.org/S4306402083","display_name":"ScholarlyCommons (University of Pennsylvania)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I79576946","host_organization_name":"University of Pennsylvania","host_organization_lineage":["https://openalex.org/I79576946"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"published","raw_type":"Report"},{"id":"mag:1563100697","doi":null,"is_oa":false,"landing_page_url":"http://pdhillon.com/graph_da_coling_2012.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306419219","display_name":"International Conference on Computational Linguistics","issn_l":"1525-2477","issn":["1525-2477"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["jufo-1"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"International Conference on Computational Linguistics","raw_type":null}],"best_oa_location":{"id":"pmh:oai:repository.upenn.edu:cis_reports-2021","doi":null,"is_oa":true,"landing_page_url":"https://repository.upenn.edu/cis_reports/975","pdf_url":"https://repository.upenn.edu/cis_reports/975","source":{"id":"https://openalex.org/S4306402083","display_name":"ScholarlyCommons (University of Pennsylvania)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I79576946","host_organization_name":"University of Pennsylvania","host_organization_lineage":["https://openalex.org/I79576946"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Technical Reports (CIS)","raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W1563100697.pdf","grobid_xml":"https://content.openalex.org/works/W1563100697.grobid-xml"},"referenced_works_count":22,"referenced_works":["https://openalex.org/W167670643","https://openalex.org/W172698429","https://openalex.org/W1552297528","https://openalex.org/W1898583019","https://openalex.org/W1998894210","https://openalex.org/W2055588122","https://openalex.org/W2098027503","https://openalex.org/W2102419107","https://openalex.org/W2104290444","https://openalex.org/W2107008379","https://openalex.org/W2107298017","https://openalex.org/W2120354757","https://openalex.org/W2130975838","https://openalex.org/W2138388365","https://openalex.org/W2139823104","https://openalex.org/W2141923507","https://openalex.org/W2155169493","https://openalex.org/W2158108973","https://openalex.org/W2165698076","https://openalex.org/W2166706824","https://openalex.org/W2169495281","https://openalex.org/W3151142710"],"related_works":["https://openalex.org/W2071162048","https://openalex.org/W2905006802","https://openalex.org/W3081123675","https://openalex.org/W4214823095","https://openalex.org/W2895187988","https://openalex.org/W2958215916","https://openalex.org/W3014788410","https://openalex.org/W3076174210","https://openalex.org/W4394842339","https://openalex.org/W4385768091"],"abstract_inverted_index":{"In":[0],"many":[1],"domain":[2,17],"adaption":[3],"formulations,":[4],"it":[5,25],"is":[6,48,146],"assumed":[7],"to":[8,50,121,148,184],"have":[9],"large":[10,30,65,104],"amount":[11,31,66],"of":[12,18,24,32,67,75,125,156,162,172,196,203],"unlabeled":[13,68,201],"data":[14,34,47,69,202],"from":[15,35,70,98],"the":[16,43,59,134,150,160,163,170,194,204],"interest":[19],"(target":[20],"domain),":[21],"some":[22,122],"portion":[23,74],"may":[26,77],"be":[27,78],"labeled,":[28],"and":[29,88,96,140,168,192,200],"labeled":[33,46,95,135,199],"other":[36],"domains,":[37,72,100,191],"aka":[38],"source":[39],"domain(s).":[40],"Motivated":[41],"by":[42],"fact":[44],"that":[45,180],"hard":[49],"obtain":[51],"in":[52,61,84,187],"any":[53],"domain,":[54],"we":[55,101,132],"design":[56],"algorithms":[57,139],"for":[58],"settings":[60],"which":[62,76,145],"there":[63],"exists":[64,112],"all":[71,93,99],"small":[73],"labeled.\\nWe":[79],"build":[80,102],"on":[81,159],"recent":[82],"advances":[83],"graph-based":[85],"semi-supervised":[86],"learning":[87],"supervised":[89],"metric":[90],"learning.":[91],"Given":[92],"instances,":[94],"unlabeled,":[97],"a":[103,142],"similarity":[105],"graph":[106],"between":[107,113],"them,":[108],"where":[109],"an":[110],"edge":[111],"two":[114,164],"instances":[115,136],"if":[116],"they":[117],"are":[118],"close":[119],"according":[120],"metric.":[123],"Instead":[124],"using":[126],"predefined":[127],"metric,":[128,144],"as":[129],"commonly":[130],"performed,":[131],"feed":[133],"into":[137],"metric-learning":[138],"(re)construct":[141],"data-dependent":[143],"used":[147],"construct":[149],"graph.":[151],"We":[152],"employ":[153],"different":[154],"types":[155],"edges":[157],"depending":[158],"domain-identity":[161],"vertices":[165],"touching":[166],"it,":[167],"learn":[169],"weights":[171],"each":[173,197],"edge.\\nWe":[174],"provide":[175],"extensive":[176],"empirical":[177],"evidence":[178],"demonstrating":[179],"our":[181],"approach":[182],"leads":[183],"significant":[185],"reduction":[186],"classification":[188],"error":[189],"across":[190],"evaluate":[193],"contribution":[195],"resource:":[198],"various":[205],"domains.":[206]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2014,"cited_by_count":1}],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2016-06-24T00:00:00"}