{"id":"https://openalex.org/W7155385770","doi":"https://doi.org/10.48550/arxiv.2604.20161","title":"SMART: A Spectral Transfer Approach to Multi-Task Learning","display_name":"SMART: A Spectral Transfer Approach to Multi-Task Learning","publication_year":2026,"publication_date":"2026-04-22","ids":{"openalex":"https://openalex.org/W7155385770","doi":"https://doi.org/10.48550/arxiv.2604.20161"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.20161","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.20161","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.20161","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5134431615","display_name":"Boxin Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Boxin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134363699","display_name":"Mladen Kolar","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kolar, Mladen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5034015361","display_name":"Jinchi Lv","orcid":"https://orcid.org/0000-0002-5881-9591"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lv, Jinchi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"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":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.7634999752044678,"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":0.7634999752044678,"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":0.04039999842643738,"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/T11289","display_name":"Single-cell and spatial transcriptomics","score":0.028699999675154686,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/linear-subspace","display_name":"Linear subspace","score":0.638700008392334},{"id":"https://openalex.org/keywords/minimax","display_name":"Minimax","score":0.6000999808311462},{"id":"https://openalex.org/keywords/source-code","display_name":"Source code","score":0.5371999740600586},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.4250999987125397},{"id":"https://openalex.org/keywords/logarithm","display_name":"Logarithm","score":0.4156999886035919},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.4052000045776367},{"id":"https://openalex.org/keywords/python","display_name":"Python (programming language)","score":0.39010000228881836},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.3725000023841858}],"concepts":[{"id":"https://openalex.org/C12362212","wikidata":"https://www.wikidata.org/wiki/Q728435","display_name":"Linear subspace","level":2,"score":0.638700008392334},{"id":"https://openalex.org/C149728462","wikidata":"https://www.wikidata.org/wiki/Q751319","display_name":"Minimax","level":2,"score":0.6000999808311462},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.5371999740600586},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.508400022983551},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4659000039100647},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.4250999987125397},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4196000099182129},{"id":"https://openalex.org/C39927690","wikidata":"https://www.wikidata.org/wiki/Q11197","display_name":"Logarithm","level":2,"score":0.4156999886035919},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.4052000045776367},{"id":"https://openalex.org/C519991488","wikidata":"https://www.wikidata.org/wiki/Q28865","display_name":"Python (programming language)","level":2,"score":0.39010000228881836},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.3725000023841858},{"id":"https://openalex.org/C92207270","wikidata":"https://www.wikidata.org/wiki/Q939253","display_name":"Matrix norm","level":3,"score":0.3571999967098236},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3562999963760376},{"id":"https://openalex.org/C109282560","wikidata":"https://www.wikidata.org/wiki/Q4166054","display_name":"Singular value","level":3,"score":0.3352999985218048},{"id":"https://openalex.org/C132964779","wikidata":"https://www.wikidata.org/wiki/Q2110223","display_name":"Raw data","level":2,"score":0.3240000009536743},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.32190001010894775},{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.31779998540878296},{"id":"https://openalex.org/C2985998994","wikidata":"https://www.wikidata.org/wiki/Q3644502","display_name":"Source model","level":2,"score":0.289000004529953},{"id":"https://openalex.org/C81299745","wikidata":"https://www.wikidata.org/wiki/Q334269","display_name":"Transfer function","level":2,"score":0.2856999933719635},{"id":"https://openalex.org/C122890649","wikidata":"https://www.wikidata.org/wiki/Q7834016","display_name":"Transfer matrix","level":2,"score":0.2851000130176544},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.2842999994754791},{"id":"https://openalex.org/C129848803","wikidata":"https://www.wikidata.org/wiki/Q2564360","display_name":"Sample size determination","level":2,"score":0.28349998593330383},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2800999879837036},{"id":"https://openalex.org/C41045048","wikidata":"https://www.wikidata.org/wiki/Q202843","display_name":"Linear programming","level":2,"score":0.26499998569488525},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.2551000118255615}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.20161","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.20161","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.20161","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.20161","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Multi-task":[0],"learning":[1,20],"is":[2,17,83,134,140,214],"effective":[3],"for":[4,49],"related":[5,25],"applications,":[6],"but":[7],"its":[8],"performance":[9],"can":[10,21],"deteriorate":[11],"when":[12,85,131],"the":[13,37,58,67,76,94,99,124,137,160,205],"target":[14,40,59,100],"sample":[15],"size":[16],"small.":[18],"Transfer":[19],"borrow":[22],"strength":[23],"from":[24,110],"studies;":[26],"yet,":[27],"many":[28],"existing":[29],"methods":[30],"rely":[31],"on":[32],"restrictive":[33],"bounded-difference":[34,95],"assumptions":[35],"between":[36],"source":[38,69,77,112,120,126],"and":[39,61,71,90,154,183,188],"models.":[41],"We":[42,148],"propose":[43],"SMART,":[44,202],"a":[45,111,118,144,155],"spectral":[46,56,108],"transfer":[47,92],"method":[48],"multi-task":[50],"linear":[51],"regression":[52],"that":[53,106],"instead":[54],"assumes":[55],"similarity:":[57],"left":[60],"right":[62],"singular":[63,78],"subspaces":[64,70],"lie":[65],"within":[66],"corresponding":[68],"are":[72],"sparsely":[73],"aligned":[74],"with":[75,204],"bases.":[79],"Such":[80],"an":[81],"assumption":[82],"natural":[84],"studies":[86],"share":[87],"latent":[88],"structures":[89],"enables":[91],"beyond":[93],"settings.":[96],"SMART":[97],"estimates":[98],"coefficient":[101],"matrix":[102],"through":[103],"structured":[104],"regularization":[105],"incorporates":[107],"information":[109],"study.":[113],"Importantly,":[114],"it":[115,129],"requires":[116],"only":[117],"fitted":[119],"model":[121],"rather":[122],"than":[123],"raw":[125],"data,":[127],"making":[128],"useful":[130],"data":[132,193],"sharing":[133],"limited.":[135],"Although":[136],"optimization":[138],"problem":[139],"nonconvex,":[141],"we":[142],"develop":[143],"practical":[145],"ADMM-based":[146],"algorithm.":[147],"establish":[149],"general,":[150],"non-asymptotic":[151],"error":[152,172],"bounds":[153],"minimax":[156],"lower":[157],"bound":[158],"in":[159,211],"noiseless-source":[161],"regime.":[162],"Under":[163],"additional":[164],"regularity":[165],"conditions,":[166],"these":[167],"results":[168],"yield":[169],"near-minimax":[170],"Frobenius":[171],"rates":[173],"up":[174],"to":[175,185,207],"logarithmic":[176],"factors.":[177],"Simulations":[178],"confirm":[179],"improved":[180],"estimation":[181],"accuracy":[182],"robustness":[184],"negative":[186],"transfer,":[187],"analysis":[189],"of":[190,201],"multi-modal":[191],"single-cell":[192],"demonstrates":[194],"better":[195],"predictive":[196],"performance.":[197],"The":[198],"Python":[199],"implementation":[200],"along":[203],"code":[206],"reproduce":[208],"all":[209],"experiments":[210],"this":[212],"paper,":[213],"publicly":[215],"available":[216],"at":[217],"https://github.com/boxinz17/smart.":[218]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-04-24T00:00:00"}