{"id":"https://openalex.org/W7131078487","doi":"https://doi.org/10.48550/arxiv.2602.17876","title":"Interactive Learning of Single-Index Models via Stochastic Gradient Descent","display_name":"Interactive Learning of Single-Index Models via Stochastic Gradient Descent","publication_year":2026,"publication_date":"2026-02-19","ids":{"openalex":"https://openalex.org/W7131078487","doi":"https://doi.org/10.48550/arxiv.2602.17876"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2602.17876","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.17876","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2602.17876","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5064641699","display_name":"Nived Rajaraman","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Rajaraman, Nived","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5126283688","display_name":"Yanjun Han","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Han, Yanjun","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5064641699"],"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.4620000123977661,"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.4620000123977661,"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":0.40119999647140503,"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"}},{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.050200000405311584,"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/stochastic-gradient-descent","display_name":"Stochastic gradient descent","score":0.7113999724388123},{"id":"https://openalex.org/keywords/regret","display_name":"Regret","score":0.59170001745224},{"id":"https://openalex.org/keywords/gradient-descent","display_name":"Gradient descent","score":0.46810001134872437},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4372999966144562},{"id":"https://openalex.org/keywords/online-machine-learning","display_name":"Online machine learning","score":0.3799000084400177},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.37790000438690186},{"id":"https://openalex.org/keywords/adaptive-learning","display_name":"Adaptive learning","score":0.3709000051021576},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.36010000109672546}],"concepts":[{"id":"https://openalex.org/C206688291","wikidata":"https://www.wikidata.org/wiki/Q7617819","display_name":"Stochastic gradient descent","level":3,"score":0.7113999724388123},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6240000128746033},{"id":"https://openalex.org/C50817715","wikidata":"https://www.wikidata.org/wiki/Q79895177","display_name":"Regret","level":2,"score":0.59170001745224},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5651999711990356},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.46810001134872437},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4372999966144562},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41440001130104065},{"id":"https://openalex.org/C115903097","wikidata":"https://www.wikidata.org/wiki/Q7094097","display_name":"Online machine learning","level":3,"score":0.3799000084400177},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.37790000438690186},{"id":"https://openalex.org/C125014702","wikidata":"https://www.wikidata.org/wiki/Q4680749","display_name":"Adaptive learning","level":2,"score":0.3709000051021576},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.36010000109672546},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.35359999537467957},{"id":"https://openalex.org/C55479107","wikidata":"https://www.wikidata.org/wiki/Q97663916","display_name":"Stochastic approximation","level":3,"score":0.3325999975204468},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.3197000026702881},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.30880001187324524},{"id":"https://openalex.org/C77967617","wikidata":"https://www.wikidata.org/wiki/Q4677561","display_name":"Active learning (machine learning)","level":2,"score":0.2904999852180481},{"id":"https://openalex.org/C34585555","wikidata":"https://www.wikidata.org/wiki/Q1368723","display_name":"Learning curve","level":2,"score":0.2888000011444092},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2831000089645386},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.2741999924182892},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.2694000005722046},{"id":"https://openalex.org/C2778334786","wikidata":"https://www.wikidata.org/wiki/Q1586270","display_name":"Variation (astronomy)","level":2,"score":0.259799987077713},{"id":"https://openalex.org/C163175372","wikidata":"https://www.wikidata.org/wiki/Q3339222","display_name":"Linear model","level":2,"score":0.25290000438690186},{"id":"https://openalex.org/C22367795","wikidata":"https://www.wikidata.org/wiki/Q7625208","display_name":"Structured prediction","level":2,"score":0.2522999942302704}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2602.17876","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.17876","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2602.17876","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.17876","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"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":{"Stochastic":[0],"gradient":[1],"descent":[2],"(SGD)":[3],"is":[4,65],"a":[5,21,66,89,109,127],"cornerstone":[6],"algorithm":[7],"for":[8,12,51,126,141],"high-dimensional":[9,31],"optimization,":[10],"renowned":[11],"its":[13,72],"empirical":[14],"successes.":[15],"Recent":[16],"theoretical":[17],"advances":[18],"have":[19],"provided":[20],"deep":[22],"understanding":[23],"of":[24,130],"how":[25],"SGD":[26,64,87,111,137],"enables":[27],"feature":[28],"learning":[29,49,73,106,142],"in":[30,98],"nonlinear":[32],"models,":[33,53],"most":[34],"notably":[35],"the":[36,47,83,95],"\\textit{single-index":[37],"model}":[38],"with":[39,102],"i.i.d.":[40],"data.":[41,147],"In":[42],"this":[43,99],"work,":[44],"we":[45],"study":[46],"sequential":[48],"problem":[50],"single-index":[52,143],"also":[54],"known":[55],"as":[56],"generalized":[57],"linear":[58],"bandits":[59],"or":[60],"ridge":[61],"bandits,":[62],"where":[63],"simple":[67],"and":[68,120],"natural":[69],"solution,":[70],"yet":[71],"dynamics":[74],"remain":[75],"largely":[76],"unexplored.":[77],"We":[78],"show":[79],"that,":[80],"similar":[81],"to":[82],"optimal":[84],"interactive":[85],"learner,":[86],"undergoes":[88],"distinct":[90],"``burn-in''":[91],"phase":[92,97],"before":[93],"entering":[94],"``learning''":[96],"setting.":[100],"Moreover,":[101],"an":[103],"appropriately":[104],"chosen":[105],"rate":[107],"schedule,":[108],"single":[110],"procedure":[112],"simultaneously":[113],"achieves":[114],"near-optimal":[115],"(or":[116],"best-known)":[117],"sample":[118],"complexity":[119],"regret":[121],"guarantees":[122],"across":[123],"both":[124],"phases,":[125],"broad":[128],"class":[129],"link":[131],"functions.":[132],"Our":[133],"results":[134],"demonstrate":[135],"that":[136],"remains":[138],"highly":[139],"competitive":[140],"models":[144],"under":[145],"adaptive":[146]},"counts_by_year":[],"updated_date":"2026-02-24T06:20:37.074948","created_date":"2026-02-24T00:00:00"}