{"id":"https://openalex.org/W4283824046","doi":"https://doi.org/10.48550/arxiv.2207.01190","title":"Pareto Optimization for Active Learning under Out-of-Distribution Data Scenarios","display_name":"Pareto Optimization for Active Learning under Out-of-Distribution Data Scenarios","publication_year":2022,"publication_date":"2022-07-04","ids":{"openalex":"https://openalex.org/W4283824046","doi":"https://doi.org/10.48550/arxiv.2207.01190"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2207.01190","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2207.01190","pdf_url":"https://arxiv.org/pdf/2207.01190","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2207.01190","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5112320070","display_name":"Xueying Zhan","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Zhan, Xueying","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035686964","display_name":"Zeyu Dai","orcid":"https://orcid.org/0000-0002-1351-476X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dai, Zeyu","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073897483","display_name":"Qingzhong Wang","orcid":"https://orcid.org/0000-0003-1562-8098"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Qingzhong","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100404176","display_name":"Qing Li","orcid":"https://orcid.org/0000-0003-3370-471X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Qing","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081254155","display_name":"Haoyi Xiong","orcid":"https://orcid.org/0000-0002-5451-3253"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiong, Haoyi","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066063885","display_name":"Dejing Dou","orcid":"https://orcid.org/0000-0001-7561-1672"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dou, Dejing","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5065680386","display_name":"Antoni B. Chan","orcid":"https://orcid.org/0000-0002-2886-2513"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chan, Antoni B.","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5112320070"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.9994000196456909,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9994000196456909,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9977999925613403,"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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9833999872207642,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6539830565452576},{"id":"https://openalex.org/keywords/oracle","display_name":"Oracle","score":0.6520010232925415},{"id":"https://openalex.org/keywords/pareto-principle","display_name":"Pareto principle","score":0.598187267780304},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5356642007827759},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.520068347454071},{"id":"https://openalex.org/keywords/multi-objective-optimization","display_name":"Multi-objective optimization","score":0.5155153274536133},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.4967702031135559},{"id":"https://openalex.org/keywords/sampling-distribution","display_name":"Sampling distribution","score":0.49462243914604187},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.49111077189445496},{"id":"https://openalex.org/keywords/optimization-problem","display_name":"Optimization problem","score":0.452043354511261},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4519944489002228},{"id":"https://openalex.org/keywords/cross-entropy","display_name":"Cross entropy","score":0.43440577387809753},{"id":"https://openalex.org/keywords/principle-of-maximum-entropy","display_name":"Principle of maximum entropy","score":0.42726999521255493},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3643626570701599},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3017089366912842},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.20654872059822083},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.200372576713562},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1964040994644165}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6539830565452576},{"id":"https://openalex.org/C55166926","wikidata":"https://www.wikidata.org/wiki/Q2892946","display_name":"Oracle","level":2,"score":0.6520010232925415},{"id":"https://openalex.org/C137635306","wikidata":"https://www.wikidata.org/wiki/Q182667","display_name":"Pareto principle","level":2,"score":0.598187267780304},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5356642007827759},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.520068347454071},{"id":"https://openalex.org/C68781425","wikidata":"https://www.wikidata.org/wiki/Q2052203","display_name":"Multi-objective optimization","level":2,"score":0.5155153274536133},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.4967702031135559},{"id":"https://openalex.org/C167723999","wikidata":"https://www.wikidata.org/wiki/Q3773214","display_name":"Sampling distribution","level":2,"score":0.49462243914604187},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.49111077189445496},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.452043354511261},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4519944489002228},{"id":"https://openalex.org/C167981619","wikidata":"https://www.wikidata.org/wiki/Q1685498","display_name":"Cross entropy","level":3,"score":0.43440577387809753},{"id":"https://openalex.org/C9679016","wikidata":"https://www.wikidata.org/wiki/Q1417473","display_name":"Principle of maximum entropy","level":2,"score":0.42726999521255493},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3643626570701599},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3017089366912842},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.20654872059822083},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.200372576713562},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1964040994644165},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2207.01190","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2207.01190","pdf_url":"https://arxiv.org/pdf/2207.01190","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"doi:10.48550/arxiv.2207.01190","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2207.01190","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2207.01190","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2207.01190","pdf_url":"https://arxiv.org/pdf/2207.01190","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2073713056","https://openalex.org/W3110702597","https://openalex.org/W2078761926","https://openalex.org/W2110441383","https://openalex.org/W2125620709","https://openalex.org/W1498872724","https://openalex.org/W4233149903","https://openalex.org/W4293864700","https://openalex.org/W2126686191","https://openalex.org/W2022485700"],"abstract_inverted_index":{"Pool-based":[0],"Active":[1,142],"Learning":[2,143,212,216],"(AL)":[3],"has":[4],"achieved":[5],"great":[6],"success":[7],"in":[8,39],"minimizing":[9],"labeling":[10],"cost":[11],"by":[12,98],"sequentially":[13],"selecting":[14],"informative":[15],"unlabeled":[16,21,46,150,158],"samples":[17,52,104,114,151],"from":[18,28,156],"a":[19,73,135,168],"large":[20],"data":[22,42,47,51,70,91,159,187],"pool":[23,48],"and":[24,85,172,193,214],"querying":[25],"their":[26],"labels":[27],"oracle/annotators.":[29],"However,":[30],"existing":[31],"AL":[32,66,82,89,164,186],"sampling":[33,83,136,165,188],"strategies":[34,84],"might":[35],"not":[36,55,198],"work":[37],"well":[38],"out-of-distribution":[40],"(OOD)":[41],"scenarios,":[43],"where":[44],"the":[45,58,61,78,99,157,163,184,195],"contains":[49],"some":[50],"that":[53,92],"do":[54],"belong":[56],"to":[57,77,95,116],"classes":[59],"of":[60,149,197],"target":[62],"task.":[63],"Achieving":[64],"good":[65],"performance":[67],"under":[68],"OOD":[69,86,113,201],"scenarios":[71],"is":[72],"challenging":[74],"task":[75,166],"due":[76],"natural":[79],"conflict":[80],"between":[81],"sample":[87],"detection.":[88],"selects":[90,146],"are":[93],"hard":[94],"be":[96],"classified":[97],"current":[100],"basic":[101],"classifier":[102],"(e.g.,":[103,190],"whose":[105],"predicted":[106,120],"class":[107,121],"probabilities":[108,122],"have":[109,117],"high":[110,124],"entropy),":[111,192],"while":[112],"tend":[115],"more":[118],"uniform":[119],"(i.e.,":[123],"entropy)":[125],"than":[126],"in-distribution":[127],"(ID)":[128],"data.":[129],"In":[130],"this":[131],"paper,":[132],"we":[133,174],"propose":[134],"scheme,":[137],"Monte-Carlo":[138],"Pareto":[139,176],"Optimization":[140],"for":[141],"(POAL),":[144],"which":[145],"optimal":[147],"subsets":[148],"with":[152],"fixed":[153],"batch":[154],"size":[155],"pool.":[160],"We":[161],"cast":[162],"as":[167],"multi-objective":[169],"optimization":[170,177],"problem,":[171],"thus":[173],"utilize":[175],"based":[178],"on":[179,208],"two":[180],"conflicting":[181],"objectives:":[182],"(1)":[183],"normal":[185],"scheme":[189],"maximum":[191],"(2)":[194],"confidence":[196],"being":[199],"an":[200],"sample.":[202],"Experimental":[203],"results":[204],"show":[205],"its":[206],"effectiveness":[207],"both":[209],"classical":[210],"Machine":[211],"(ML)":[213],"Deep":[215],"(DL)":[217],"tasks.":[218]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2026-02-09T09:26:11.010843","created_date":"2022-07-07T00:00:00"}
