{"id":"https://openalex.org/W6992043070","doi":null,"title":"ISR: INVARIANT SUBSPACE RECOVERY","display_name":"ISR: INVARIANT SUBSPACE RECOVERY","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W6992043070"},"language":"en","primary_location":{"id":"pmh:oai:www.ideals.illinois.edu:2142/115006","doi":null,"is_oa":true,"landing_page_url":"https://hdl.handle.net/2142/115006","pdf_url":"https://www.ideals.illinois.edu/items/124423/bitstreams/409180/data.pdf","source":{"id":"https://openalex.org/S4306401358","display_name":"Illinois Digital Environment for Access to Learning and Scholarship (University of Illinois at Urbana-Champaign)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I2801919071","host_organization_name":"University of Illinois System","host_organization_lineage":["https://openalex.org/I2801919071"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"dissertation/thesis"},"volume":null,"type":"dissertation","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://www.ideals.illinois.edu/items/124423/bitstreams/409180/data.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5056418488","display_name":"Haozhe Si","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Si, Haozhe","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5056418488"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"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":true,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9994999766349792,"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":0.9994999766349792,"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.0,"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.0,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/domain-generalization","display_name":"domain generalization","score":0.8939999938011169},{"id":"https://openalex.org/keywords/invariant-risk-minimization","display_name":"invariant risk minimization","score":0.9639999866485596},{"id":"https://openalex.org/keywords/spurious-features","display_name":"spurious features","score":0.9419999718666077},{"id":"https://openalex.org/keywords/convergence-guarantees","display_name":"convergence guarantees","score":0.6549999713897705}],"concepts":[{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.6703000068664551},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.6567999720573425},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5986999869346619},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.539900004863739},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.517799973487854},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5073000192642212},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4893999993801117},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4462999999523163},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4277999997138977},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4120999872684479},{"id":"https://openalex.org/C16910744","wikidata":"https://www.wikidata.org/wiki/Q7705759","display_name":"Test data","level":2,"score":0.3971000015735626},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.38850000500679016},{"id":"https://openalex.org/C2777059694","wikidata":"https://www.wikidata.org/wiki/Q2706744","display_name":"Invariant subspace","level":3,"score":0.38499999046325684},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37529999017715454},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.36010000109672546},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.35019999742507935},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.3452000021934509},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.320499986410141},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.3059000074863434},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2994999885559082},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.289900004863739},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2754000127315521},{"id":"https://openalex.org/C19118579","wikidata":"https://www.wikidata.org/wiki/Q786423","display_name":"Frequency domain","level":2,"score":0.27379998564720154},{"id":"https://openalex.org/C117765406","wikidata":"https://www.wikidata.org/wiki/Q5362437","display_name":"Generalization error","level":3,"score":0.2556999921798706},{"id":"https://openalex.org/C119322782","wikidata":"https://www.wikidata.org/wiki/Q2662236","display_name":"VC dimension","level":2,"score":0.25279998779296875},{"id":"https://openalex.org/C106135958","wikidata":"https://www.wikidata.org/wiki/Q7291993","display_name":"Random subspace method","level":3,"score":0.25049999356269836}],"mesh":[],"locations_count":3,"locations":[{"id":"pmh:oai:www.ideals.illinois.edu:2142/115006","doi":null,"is_oa":true,"landing_page_url":"https://hdl.handle.net/2142/115006","pdf_url":"https://www.ideals.illinois.edu/items/124423/bitstreams/409180/data.pdf","source":{"id":"https://openalex.org/S4306401358","display_name":"Illinois Digital Environment for Access to Learning and Scholarship (University of Illinois at Urbana-Champaign)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I2801919071","host_organization_name":"University of Illinois System","host_organization_lineage":["https://openalex.org/I2801919071"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"dissertation/thesis"},{"id":"pmh:oai:www.ideals.illinois.edu:2142/124978","doi":null,"is_oa":true,"landing_page_url":"https://hdl.handle.net/2142/124978","pdf_url":"https://www.ideals.illinois.edu/items/132077/bitstreams/438298/data.pdf","source":{"id":"https://openalex.org/S4306401358","display_name":"Illinois Digital Environment for Access to Learning and Scholarship (University of Illinois at Urbana-Champaign)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I2801919071","host_organization_name":"University of Illinois System","host_organization_lineage":["https://openalex.org/I2801919071"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"dissertation/thesis"},{"id":"pmh:oai:www.ideals.illinois.edu:2142/113503","doi":null,"is_oa":false,"landing_page_url":"http://hdl.handle.net/2142/113503","pdf_url":null,"source":{"id":"https://openalex.org/S4306401358","display_name":"Illinois Digital Environment for Access to Learning and Scholarship (University of Illinois at Urbana-Champaign)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I2801919071","host_organization_name":"University of Illinois System","host_organization_lineage":["https://openalex.org/I2801919071"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"dissertation/thesis"}],"best_oa_location":{"id":"pmh:oai:www.ideals.illinois.edu:2142/115006","doi":null,"is_oa":true,"landing_page_url":"https://hdl.handle.net/2142/115006","pdf_url":"https://www.ideals.illinois.edu/items/124423/bitstreams/409180/data.pdf","source":{"id":"https://openalex.org/S4306401358","display_name":"Illinois Digital Environment for Access to Learning and Scholarship (University of Illinois at Urbana-Champaign)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I2801919071","host_organization_name":"University of Illinois System","host_organization_lineage":["https://openalex.org/I2801919071"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"dissertation/thesis"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W6992043070.pdf","grobid_xml":"https://content.openalex.org/works/W6992043070.grobid-xml"},"referenced_works_count":12,"referenced_works":["https://openalex.org/W2607892599","https://openalex.org/W2953494151","https://openalex.org/W2991497298","https://openalex.org/W3030163527","https://openalex.org/W3034791248","https://openalex.org/W3109339436","https://openalex.org/W3133542152","https://openalex.org/W3134417895","https://openalex.org/W3176800135","https://openalex.org/W3196850540","https://openalex.org/W4289639938","https://openalex.org/W7133198412"],"related_works":["https://openalex.org/W4221159499","https://openalex.org/W4388328960","https://openalex.org/W7220828796","https://openalex.org/W4387870607","https://openalex.org/W2155858138","https://openalex.org/W7133198412","https://openalex.org/W3191808899","https://openalex.org/W4399554942","https://openalex.org/W3169315049","https://openalex.org/W7170552257"],"abstract_inverted_index":{"Domain":[0],"generalization":[1,111],"asks":[2],"for":[3,37],"models":[4,115,185],"trained":[5],"on":[6,15,140,162,173],"a":[7,20,98,108,129,176],"set":[8],"of":[9,22,51,77,144,183],"training":[10,70,118,157],"environments":[11,67],"to":[12,65],"perform":[13],"well":[14],"unseen":[16,66,187],"test":[17,188],"environments.":[18,119,158],"Recently,":[19],"series":[21],"algorithms":[23,41,84],"such":[24],"as":[25,175],"Invariant":[26,52,101],"Risk":[27,50,53],"Minimization":[28,54],"(IRM)":[29],"and":[30,123,165],"its":[31,124],"follow-up":[32],"works":[33],"have":[34],"been":[35],"proposed":[36,149],"domain":[38,110],"generalization.":[39],"These":[40],"are":[42,85],"empirically":[43],"successful,":[44],"however,":[45],"under":[46,112],"certain":[47],"assumptions.":[48],"The":[49],"(Rosenfeld":[55],"et":[56],"al.":[57],"2021)":[58],"shows":[59],"that":[60,105,152,170],"IRMandits":[61],"alternatives":[62],"cannot":[63],"generalize":[64],"with":[68,116,155],"opdsq":[69],"environments,":[71],"where":[72],"ds":[73],"is":[74],"the":[75,78,141,181],"dimension":[76],"spurious":[79],"feature":[80],"space.":[81],"Meanwhile,":[82],"these":[83],"computationally":[86],"costly":[87],"given":[88],"their":[89],"complex":[90],"optimization":[91],"objectives.":[92],"In":[93],"this":[94],"paper,":[95],"we":[96,147],"propose":[97],"novel":[99],"algorithm,":[100],"Subspace":[102],"Recovery":[103],"(ISR),":[104],"can":[106,153,179],"achieve":[107],"provable":[109],"Gaussian":[113],"data":[114,145,168],"Opdsq":[117],"Notably,":[120],"unlike":[121],"IRM":[122],"alternatives,":[125],"our":[126],"algorithm":[127,151],"has":[128],"global":[130],"convergence":[131],"guarantee":[132],"without":[133],"any":[134],"non-convexity":[135],"issue.":[136],"By":[137],"making":[138],"assumptions":[139],"second-order":[142],"moment":[143],"distribution,":[146],"further":[148],"an":[150],"work":[154],"Op1q":[156],"Our":[159],"experiment":[160],"results":[161],"both":[163],"synthesized":[164],"real-world":[166],"image":[167],"show":[169],"applying":[171],"ISR":[172],"features":[174],"post-processing":[177],"method":[178],"increase":[180],"accuracy":[182],"neural":[184],"in":[186],"domains.":[189]},"counts_by_year":[],"updated_date":"2026-11-11T12:16:26.678958","created_date":"2025-10-10T00:00:00"}
