{"id":"https://openalex.org/W7160948035","doi":"https://doi.org/10.48550/arxiv.2605.10151","title":"Learning to Sparsify Stochastic Linear Bandits","display_name":"Learning to Sparsify Stochastic Linear Bandits","publication_year":2026,"publication_date":"2026-05-11","ids":{"openalex":"https://openalex.org/W7160948035","doi":"https://doi.org/10.48550/arxiv.2605.10151"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.10151","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.10151","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":null,"license_id":null,"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.2605.10151","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5051587486","display_name":"Z. Jane Wang","orcid":"https://orcid.org/0000-0002-3791-0249"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Zhengmiao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135963919","display_name":"Ming Chi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chi, Ming","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100321249","display_name":"Zhi\u2010Wei Liu","orcid":"https://orcid.org/0000-0003-3005-1792"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Zhi-Wei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043334116","display_name":"Lintao Ye","orcid":"https://orcid.org/0000-0001-8608-5815"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ye, Lintao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5021780258","display_name":"Carla Fabiana Chiasserini","orcid":"https://orcid.org/0000-0003-1410-660X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chiasserini, Carla Fabiana","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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9819999933242798,"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"}},"topics":[{"id":"https://openalex.org/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9819999933242798,"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.00839999970048666,"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/T11413","display_name":"Risk and Portfolio Optimization","score":0.002199999988079071,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/greedy-algorithm","display_name":"Greedy algorithm","score":0.5896999835968018},{"id":"https://openalex.org/keywords/regret","display_name":"Regret","score":0.5512999892234802},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4828000068664551},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.482699990272522},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4596000015735626},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.3930000066757202},{"id":"https://openalex.org/keywords/convex-optimization","display_name":"Convex optimization","score":0.3905999958515167},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.3837999999523163},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.36410000920295715}],"concepts":[{"id":"https://openalex.org/C51823790","wikidata":"https://www.wikidata.org/wiki/Q504353","display_name":"Greedy algorithm","level":2,"score":0.5896999835968018},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5863999724388123},{"id":"https://openalex.org/C50817715","wikidata":"https://www.wikidata.org/wiki/Q79895177","display_name":"Regret","level":2,"score":0.5512999892234802},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4832000136375427},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4828000068664551},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.482699990272522},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4596000015735626},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.3930000066757202},{"id":"https://openalex.org/C157972887","wikidata":"https://www.wikidata.org/wiki/Q463359","display_name":"Convex optimization","level":3,"score":0.3905999958515167},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.38659998774528503},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.3837999999523163},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.36410000920295715},{"id":"https://openalex.org/C112680207","wikidata":"https://www.wikidata.org/wiki/Q714886","display_name":"Regular polygon","level":2,"score":0.3610999882221222},{"id":"https://openalex.org/C28761237","wikidata":"https://www.wikidata.org/wiki/Q7805321","display_name":"Time horizon","level":2,"score":0.3467000126838684},{"id":"https://openalex.org/C206194317","wikidata":"https://www.wikidata.org/wiki/Q1138624","display_name":"Convex hull","level":3,"score":0.3427000045776367},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.3328000009059906},{"id":"https://openalex.org/C41045048","wikidata":"https://www.wikidata.org/wiki/Q202843","display_name":"Linear programming","level":2,"score":0.3269999921321869},{"id":"https://openalex.org/C148764684","wikidata":"https://www.wikidata.org/wiki/Q621751","display_name":"Approximation algorithm","level":2,"score":0.3221000134944916},{"id":"https://openalex.org/C186450821","wikidata":"https://www.wikidata.org/wiki/Q17295","display_name":"Euclidean space","level":2,"score":0.30889999866485596},{"id":"https://openalex.org/C100808899","wikidata":"https://www.wikidata.org/wiki/Q1192100","display_name":"Set cover problem","level":3,"score":0.2964000105857849},{"id":"https://openalex.org/C17020691","wikidata":"https://www.wikidata.org/wiki/Q139677","display_name":"Operator (biology)","level":5,"score":0.29589998722076416},{"id":"https://openalex.org/C49870271","wikidata":"https://www.wikidata.org/wiki/Q193657","display_name":"Convex set","level":4,"score":0.2939999997615814},{"id":"https://openalex.org/C145446738","wikidata":"https://www.wikidata.org/wiki/Q319913","display_name":"Convex function","level":3,"score":0.29109999537467957},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.2705000042915344},{"id":"https://openalex.org/C149810388","wikidata":"https://www.wikidata.org/wiki/Q5374873","display_name":"Emulation","level":2,"score":0.25760000944137573},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.25360000133514404},{"id":"https://openalex.org/C2778770139","wikidata":"https://www.wikidata.org/wiki/Q1966904","display_name":"Solver","level":2,"score":0.2529999911785126}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.10151","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.10151","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.10151","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.10151","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.7306829690933228,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"This":[0],"paper":[1],"addresses":[2],"the":[3,28,34,47,57,62,89,113,116,122,174,178,184],"problem":[4],"of":[5,30,50,61,115,177,186],"learning":[6,80],"to":[7,23,56,105,173,195],"sparsify":[8],"stochastic":[9],"linear":[10],"bandits,":[11],"where":[12,110,133,170],"a":[13,19,24,93,107,142,153,166],"decision-maker":[14],"sequentially":[15],"selects":[16],"actions":[17,54,98,137],"from":[18],"high-dimensional":[20],"space":[21],"subject":[22],"sparsity":[25],"constraint":[26],"on":[27],"number":[29],"nonzero":[31],"elements":[32],"in":[33,41],"action":[35,86,90,117,131,149],"vector.":[36],"The":[37],"key":[38],"challenge":[39],"lies":[40],"minimizing":[42],"cumulative":[43],"regret":[44],"while":[45],"tackling":[46],"potential":[48],"NP-hardness":[49],"finding":[51,134],"optimal":[52,96,135],"sparse":[53,85,97,136],"due":[55],"inherent":[58],"combinatorial":[59],"structure":[60],"problem.":[63],"We":[64],"propose":[65],"an":[66,193],"adaptively":[67],"phased":[68],"exploration":[69],"and":[70,81,119,129],"exploitation":[71],"algorithmic":[72],"framework,":[73],"utilizing":[74],"ordinary":[75],"least":[76],"squares":[77],"for":[78,84,157],"parameter":[79],"specialized":[82],"subroutines":[83],"selection.":[87],"When":[88],"set":[91],"is":[92,112,121,138],"Euclidean":[94],"ball,":[95],"can":[99],"be":[100],"efficiently":[101],"computed,":[102],"enabling":[103],"us":[104],"establish":[106,165],"$\\tilde{\\mathcal{O}}(d\\sqrt{T})$":[108],"regret,":[109],"$d$":[111],"dimension":[114],"vector":[118],"$T$":[120],"time":[123],"horizon":[124],"length.":[125],"For":[126,145],"general":[127,146,158],"convex":[128,148],"compact":[130,159],"sets":[132,160],"intractable,":[139],"we":[140,151,164,182],"employ":[141],"greedy":[143,179],"subroutine.":[144],"strongly":[147],"sets,":[150],"derive":[152],"$\\tilde{\\mathcal{O}}(d":[154,167],"\\sqrt{T})$":[155],"$\u03b1$-regret;":[156],"lacking":[161],"strong":[162],"convexity,":[163],"T^{2/3})$":[168],"$\u03b1$-regret,":[169],"$\u03b1$":[171],"pertains":[172],"approximation":[175],"ratio":[176],"algorithm.":[180],"Finally,":[181],"validate":[183],"performance":[185],"our":[187],"algorithms":[188],"using":[189],"extensive":[190],"experiments":[191],"including":[192],"application":[194],"recommendation":[196],"system.":[197]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-13T00:00:00"}