{"id":"https://openalex.org/W4385767903","doi":"https://doi.org/10.24963/ijcai.2023/525","title":"Prediction with Incomplete Data under Agnostic Mask Distribution Shift","display_name":"Prediction with Incomplete Data under Agnostic Mask Distribution Shift","publication_year":2023,"publication_date":"2023-08-01","ids":{"openalex":"https://openalex.org/W4385767903","doi":"https://doi.org/10.24963/ijcai.2023/525"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2023/525","is_oa":true,"landing_page_url":"http://dx.doi.org/10.24963/ijcai.2023/525","pdf_url":"https://www.ijcai.org/proceedings/2023/0525.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.ijcai.org/proceedings/2023/0525.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100611386","display_name":"Yichen Zhu","orcid":"https://orcid.org/0000-0003-3614-1537"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yichen Zhu","raw_affiliation_strings":["Shanghai Jiao Tong University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100347994","display_name":"Jian Yuan","orcid":"https://orcid.org/0000-0001-9734-6056"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Yuan","raw_affiliation_strings":["Shanghai Jiao Tong University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100669526","display_name":"Bo Jiang","orcid":"https://orcid.org/0000-0001-6711-4342"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Jiang","raw_affiliation_strings":["Shanghai Jiao Tong University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101944426","display_name":"Tao Lin","orcid":"https://orcid.org/0000-0003-1170-636X"},"institutions":[{"id":"https://openalex.org/I75689368","display_name":"Communication University of China","ror":"https://ror.org/04facbs33","country_code":"CN","type":"education","lineage":["https://openalex.org/I75689368"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Lin","raw_affiliation_strings":["Communication University of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Communication University of China","institution_ids":["https://openalex.org/I75689368"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101778761","display_name":"Haiming Jin","orcid":"https://orcid.org/0000-0001-5178-7198"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haiming Jin","raw_affiliation_strings":["Shanghai Jiao Tong University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034483183","display_name":"Xinbing Wang","orcid":"https://orcid.org/0000-0002-0357-8356"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinbing Wang","raw_affiliation_strings":["Shanghai Jiao Tong University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023919188","display_name":"Chenghu Zhou","orcid":"https://orcid.org/0000-0003-3331-2302"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenghu Zhou","raw_affiliation_strings":["Shanghai Jiao Tong University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"4720","last_page":"4728"},"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":0.9987999796867371,"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":0.9987999796867371,"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":0.9984999895095825,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9955000281333923,"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/leverage","display_name":"Leverage (statistics)","score":0.742558479309082},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7129350900650024},{"id":"https://openalex.org/keywords/decorrelation","display_name":"Decorrelation","score":0.6499416828155518},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.6154828667640686},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4961422383785248},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.4689476191997528},{"id":"https://openalex.org/keywords/invariant","display_name":"Invariant (physics)","score":0.46066585183143616},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3773367702960968},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.368995726108551},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.34653159976005554},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.32651615142822266},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18422266840934753}],"concepts":[{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.742558479309082},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7129350900650024},{"id":"https://openalex.org/C177860922","wikidata":"https://www.wikidata.org/wiki/Q788608","display_name":"Decorrelation","level":2,"score":0.6499416828155518},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.6154828667640686},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4961422383785248},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.4689476191997528},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.46066585183143616},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3773367702960968},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.368995726108551},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34653159976005554},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.32651615142822266},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18422266840934753},{"id":"https://openalex.org/C37914503","wikidata":"https://www.wikidata.org/wiki/Q156495","display_name":"Mathematical physics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.24963/ijcai.2023/525","is_oa":true,"landing_page_url":"http://dx.doi.org/10.24963/ijcai.2023/525","pdf_url":"https://www.ijcai.org/proceedings/2023/0525.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2023/525","is_oa":true,"landing_page_url":"http://dx.doi.org/10.24963/ijcai.2023/525","pdf_url":"https://www.ijcai.org/proceedings/2023/0525.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320329139","display_name":"Communication University of China","ror":"https://ror.org/04facbs33"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4385767903.pdf"},"referenced_works_count":20,"referenced_works":["https://openalex.org/W91088564","https://openalex.org/W1779483307","https://openalex.org/W1959608418","https://openalex.org/W1995880999","https://openalex.org/W2112796928","https://openalex.org/W2165698076","https://openalex.org/W2803403013","https://openalex.org/W2807992610","https://openalex.org/W2885707361","https://openalex.org/W2952727443","https://openalex.org/W2963925452","https://openalex.org/W2964132737","https://openalex.org/W2997591099","https://openalex.org/W2997746169","https://openalex.org/W3055680528","https://openalex.org/W3091808145","https://openalex.org/W4285079610","https://openalex.org/W4287210705","https://openalex.org/W4294568686","https://openalex.org/W4320013936"],"related_works":["https://openalex.org/W1604939135","https://openalex.org/W2127058578","https://openalex.org/W2098040275","https://openalex.org/W2735368845","https://openalex.org/W2089764958","https://openalex.org/W3109905219","https://openalex.org/W2073586885","https://openalex.org/W2546477360","https://openalex.org/W2359691516","https://openalex.org/W2261979314"],"abstract_inverted_index":{"Data":[0],"with":[1,17,58],"missing":[2,31,86],"values":[3],"is":[4,82,110,188],"ubiquitous":[5],"in":[6,49,61],"many":[7],"applications.":[8],"Recent":[9],"years":[10],"have":[11],"witnessed":[12],"increasing":[13],"attention":[14],"on":[15,69,148,179],"prediction":[16,57,173],"only":[18],"incomplete":[19,59],"data":[20,60],"consisting":[21],"of":[22,64,77,141],"observed":[23],"features":[24,79,155],"and":[25,39,80,96,152,156,182,190],"a":[26,131,171],"mask":[27,89,196],"that":[28,36,105,153,186],"indicates":[29],"the":[30,37,43,62,70,73,85,103,117,126,137,143,149,166],"pattern.":[32],"Existing":[33],"methods":[34,193],"assume":[35],"training":[38,95],"testing":[40],"distributions":[41],"are":[42],"same,":[44],"which":[45],"may":[46,91],"be":[47],"violated":[48],"real-world":[50,183],"scenarios.":[51],"In":[52],"this":[53,163],"paper,":[54],"we":[55,101,124,169],"consider":[56],"presence":[63],"distribution":[65,76,90,197],"shift.":[66,198],"We":[67,158],"focus":[68],"case":[71],"where":[72],"underlying":[74],"joint":[75],"complete":[78],"label":[81],"invariant,":[83],"but":[84],"pattern,":[87],"i.e.,":[88],"shift":[92],"agnostically":[93],"between":[94,154],"testing.":[97],"To":[98,115],"achieve":[99],"generalization,":[100],"leverage":[102],"observation":[104],"for":[106],"each":[107],"mask,":[108],"there":[109],"an":[111],"invariant":[112],"optimal":[113,127],"predictor.":[114],"avoid":[116],"exponential":[118],"explosion":[119],"when":[120],"learning":[121],"them":[122],"separately,":[123],"approximate":[125],"predictors":[128,145],"jointly":[129],"using":[130],"double":[132],"parameterization":[133],"technique.":[134],"This":[135],"has":[136],"undesirable":[138],"side":[139],"effect":[140],"allowing":[142],"learned":[144],"to":[146,161],"rely":[147],"intra-mask":[150],"correlation":[151],"mask.":[157],"perform":[159],"decorrelation":[160],"minimize":[162],"effect.":[164],"Combining":[165],"techniques":[167],"above,":[168],"propose":[170],"novel":[172],"method":[174],"called":[175],"StableMiss.":[176],"Extensive":[177],"experiments":[178],"both":[180],"synthetic":[181],"datasets":[184],"show":[185],"StableMiss":[187],"robust":[189],"outperforms":[191],"state-of-the-art":[192],"under":[194],"agnostic":[195]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
