{"id":"https://openalex.org/W7165165161","doi":"https://doi.org/10.1145/3744256.3812562","title":"Probabilistic Hypothesis Anchored Domain Adaptation for Modeling Human Behavior","display_name":"Probabilistic Hypothesis Anchored Domain Adaptation for Modeling Human Behavior","publication_year":2026,"publication_date":"2026-06-19","ids":{"openalex":"https://openalex.org/W7165165161","doi":"https://doi.org/10.1145/3744256.3812562"},"language":null,"primary_location":{"id":"doi:10.1145/3744256.3812562","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3744256.3812562","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 13th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3744256.3812562","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5107181128","display_name":"Naailah Mahamoodally","orcid":null},"institutions":[{"id":"https://openalex.org/I60158472","display_name":"Concordia University","ror":"https://ror.org/0420zvk78","country_code":"CA","type":"education","lineage":["https://openalex.org/I60158472"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Naailah Mahamoodally","raw_affiliation_strings":["Concordia University, Montreal, QC, Canada"],"raw_orcid":"https://orcid.org/0009-0005-6186-0244","affiliations":[{"raw_affiliation_string":"Concordia University, Montreal, QC, Canada","institution_ids":["https://openalex.org/I60158472"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008962576","display_name":"Manar Amayri","orcid":"https://orcid.org/0000-0002-5610-8833"},"institutions":[{"id":"https://openalex.org/I60158472","display_name":"Concordia University","ror":"https://ror.org/0420zvk78","country_code":"CA","type":"education","lineage":["https://openalex.org/I60158472"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Manar Amayri","raw_affiliation_strings":["Concordia University, Montreal, QC, Canada"],"raw_orcid":"https://orcid.org/0000-0002-5610-8833","affiliations":[{"raw_affiliation_string":"Concordia University, Montreal, QC, Canada","institution_ids":["https://openalex.org/I60158472"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5090600716","display_name":"Nizar Bouguila","orcid":"https://orcid.org/0000-0001-7224-7940"},"institutions":[{"id":"https://openalex.org/I60158472","display_name":"Concordia University","ror":"https://ror.org/0420zvk78","country_code":"CA","type":"education","lineage":["https://openalex.org/I60158472"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Nizar Bouguila","raw_affiliation_strings":["Concordia Institute for Information Systems Engineering, Montreal, QC, Canada"],"raw_orcid":"https://orcid.org/0000-0001-7224-7940","affiliations":[{"raw_affiliation_string":"Concordia Institute for Information Systems Engineering, Montreal, QC, Canada","institution_ids":["https://openalex.org/I60158472"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.95056394,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"24","last_page":"34"},"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":0.4708999991416931,"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":0.4708999991416931,"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/T11448","display_name":"Face recognition and analysis","score":0.07209999859333038,"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.031599998474121094,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5418000221252441},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.517300009727478},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.3343000113964081},{"id":"https://openalex.org/keywords/statistical-model","display_name":"Statistical model","score":0.3255000114440918},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.25839999318122864}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6021000146865845},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5418000221252441},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5329999923706055},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.517300009727478},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.3343000113964081},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.3255000114440918},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32010000944137573},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.25839999318122864},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.24719999730587006},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.2345000058412552}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3744256.3812562","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3744256.3812562","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 13th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3744256.3812562","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3744256.3812562","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 13th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W2475772748","https://openalex.org/W2811153818","https://openalex.org/W2969893028","https://openalex.org/W2971069864","https://openalex.org/W2991405316","https://openalex.org/W3041133507","https://openalex.org/W3092609815","https://openalex.org/W3118468178","https://openalex.org/W3130794141","https://openalex.org/W3180849682","https://openalex.org/W3194446231","https://openalex.org/W3207924781","https://openalex.org/W3213330479","https://openalex.org/W3213908205","https://openalex.org/W3215947932","https://openalex.org/W4207065329","https://openalex.org/W4210371417","https://openalex.org/W4214715922","https://openalex.org/W4221138878","https://openalex.org/W4224224459","https://openalex.org/W4292198371","https://openalex.org/W4296301579","https://openalex.org/W4296640192","https://openalex.org/W4304092624","https://openalex.org/W4304689967","https://openalex.org/W4311404181","https://openalex.org/W4316660917","https://openalex.org/W4319299795","https://openalex.org/W4379091230","https://openalex.org/W4385076727","https://openalex.org/W4386057716","https://openalex.org/W4392251648","https://openalex.org/W4392655270","https://openalex.org/W4394935142","https://openalex.org/W4401009936","https://openalex.org/W4402509619","https://openalex.org/W4412535621"],"related_works":[],"abstract_inverted_index":{"Energy-efficient":[0],"smart":[1,142],"buildings":[2],"depend":[3],"on":[4,140,184],"accurate":[5],"modeling":[6,90],"of":[7,57,163],"human":[8],"behavior,":[9],"such":[10,34],"as":[11,122],"occupancy":[12],"and":[13,20,47,52,63,105,132,154],"activity":[14],"patterns,":[15],"to":[16,39,69,94,175],"manage":[17],"resources":[18],"intelligently":[19],"reduce":[21],"overall":[22],"energy":[23],"consumption":[24],"while":[25,157],"maintaining":[26],"occupant":[27,48],"comfort.":[28],"However,":[29],"achieving":[30],"robust":[31,96],"performance":[32,131],"in":[33,44],"models":[35],"remains":[36],"challenging":[37],"due":[38],"scarce":[40],"labeled":[41],"data,":[42],"variations":[43],"sensor":[45,59],"configurations":[46],"behavior":[49,183],"across":[50,126],"buildings,":[51],"the":[53,123,161,164,185],"high-dimensional,":[54],"non-linear":[55],"nature":[56],"multimodal":[58],"data.":[60,72],"Furthermore,":[61],"privacy":[62],"data-sharing":[64],"constraints":[65],"further":[66,169],"limit":[67],"access":[68],"raw":[70],"building":[71,143],"To":[73],"address":[74],"these":[75],"challenges,":[76],"we":[77],"propose":[78],"PHADA":[79,100,147],"(Probabilistic":[80],"Hypothesis-Anchored":[81],"Domain":[82],"Adaptation),":[83],"a":[84,102,112,171],"source-free":[85],"framework":[86],"that":[87,117,146],"integrates":[88],"probabilistic":[89],"with":[91,111],"hypothesis":[92],"transfer":[93],"enable":[95],"unsupervised":[97,108],"domain":[98,137,152,178],"adaptation.":[99],"leverages":[101],"Semi-MPPCA":[103],"backbone":[104],"introduces":[106],"an":[107],"adaptation":[109,179],"stage":[110],"novel":[113],"component-anchor":[114],"alignment":[115],"mechanism":[116],"maintains":[118],"coherent":[119],"latent":[120],"structure":[121],"model":[124,181],"transfers":[125],"domains.":[127],"This":[128],"design":[129,166],"improves":[130],"reduces":[133],"class":[134],"collapse":[135],"under":[136,151],"shift.":[138],"Experiments":[139],"multi-environment":[141],"datasets":[144],"show":[145],"outperforms":[148],"state-of-the-art":[149],"baselines":[150],"shift":[153],"label":[155],"scarcity,":[156],"ablation":[158],"studies":[159],"demonstrate":[160],"impact":[162],"proposed":[165],"choices.":[167],"We":[168],"include":[170],"post-hoc":[172],"feature-level":[173],"analysis":[174],"examine":[176],"how":[177],"affects":[180],"decision":[182],"target":[186],"domain.":[187],"Code":[188],"will":[189],"be":[190],"released":[191],"upon":[192],"acceptance.":[193]},"counts_by_year":[],"updated_date":"2026-06-20T20:08:15.867695","created_date":"2026-06-19T00:00:00"}
