{"id":"https://openalex.org/W7160965952","doi":"https://doi.org/10.48550/arxiv.2605.09588","title":"Efficient Ensemble Selection from Binary and Pairwise Feedback","display_name":"Efficient Ensemble Selection from Binary and Pairwise Feedback","publication_year":2026,"publication_date":"2026-05-10","ids":{"openalex":"https://openalex.org/W7160965952","doi":"https://doi.org/10.48550/arxiv.2605.09588"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.09588","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.09588","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":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.09588","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5135997505","display_name":"Tzeh Yuan Neoh","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Neoh, Tzeh Yuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135945249","display_name":"Nicholas Teh","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Teh, Nicholas","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5120411975","display_name":"Je Qin Chooi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chooi, Je Qin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067662147","display_name":"Paul W. Goldberg","orcid":"https://orcid.org/0000-0002-5436-7890"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Goldberg, Paul W.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5135977549","display_name":"Milind Tambe","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tambe, Milind","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"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/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.526199996471405,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.526199996471405,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/T10883","display_name":"Ethics and Social Impacts of AI","score":0.08209999650716782,"subfield":{"id":"https://openalex.org/subfields/3311","display_name":"Safety Research"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11596","display_name":"Constraint Satisfaction and Optimization","score":0.06279999762773514,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/pairwise-comparison","display_name":"Pairwise comparison","score":0.8349000215530396},{"id":"https://openalex.org/keywords/oracle","display_name":"Oracle","score":0.6355999708175659},{"id":"https://openalex.org/keywords/submodular-set-function","display_name":"Submodular set function","score":0.552299976348877},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.4862000048160553},{"id":"https://openalex.org/keywords/greedy-algorithm","display_name":"Greedy algorithm","score":0.4690999984741211},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4657000005245209},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4634999930858612},{"id":"https://openalex.org/keywords/minimax","display_name":"Minimax","score":0.44519999623298645}],"concepts":[{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.8349000215530396},{"id":"https://openalex.org/C55166926","wikidata":"https://www.wikidata.org/wiki/Q2892946","display_name":"Oracle","level":2,"score":0.6355999708175659},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5983999967575073},{"id":"https://openalex.org/C178621042","wikidata":"https://www.wikidata.org/wiki/Q7631710","display_name":"Submodular set function","level":2,"score":0.552299976348877},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.4862000048160553},{"id":"https://openalex.org/C51823790","wikidata":"https://www.wikidata.org/wiki/Q504353","display_name":"Greedy algorithm","level":2,"score":0.4690999984741211},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4657000005245209},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4634999930858612},{"id":"https://openalex.org/C149728462","wikidata":"https://www.wikidata.org/wiki/Q751319","display_name":"Minimax","level":2,"score":0.44519999623298645},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.4235999882221222},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3977999985218048},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.38679999113082886},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.38449999690055847},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.3686000108718872},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.3264000117778778},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.321399986743927},{"id":"https://openalex.org/C2776330181","wikidata":"https://www.wikidata.org/wiki/Q18358244","display_name":"Maximization","level":2,"score":0.311599999666214},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3077999949455261},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2994000017642975},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.2989000082015991},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.28209999203681946},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.2777999937534332},{"id":"https://openalex.org/C157692150","wikidata":"https://www.wikidata.org/wiki/Q2919848","display_name":"Query optimization","level":2,"score":0.27559998631477356},{"id":"https://openalex.org/C2834757","wikidata":"https://www.wikidata.org/wiki/Q4925424","display_name":"Monotone polygon","level":2,"score":0.27480000257492065},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.27320000529289246},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.26190000772476196},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.2583000063896179},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.25679999589920044}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.09588","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.09588","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":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.09588","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.09588","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":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Organizations":[0],"increasingly":[1],"deploy":[2],"multiple":[3],"AI":[4],"systems":[5],"across":[6],"task":[7,46,58],"domains,":[8],"but":[9,140,151],"selecting":[10],"a":[11,31,53,57,109,138,156,166,186],"small,":[12],"high-performing":[13],"ensemble":[14],"can":[15],"require":[16],"costly":[17],"model":[18],"calls,":[19],"benchmark":[20],"runs,":[21],"and":[22,52,75,100,106,145,164,200],"human":[23],"evaluation.":[24],"We":[25,65,96,132,173,189],"study":[26,129],"this":[27,176],"selection":[28],"problem":[29],"as":[30],"distributional":[32],"variant":[33],"of":[34,203],"multiwinner":[35],"voting:":[36],"tasks":[37,71,79],"are":[38,83],"drawn":[39],"from":[40],"an":[41],"unknown":[42],"domain":[43],"distribution,":[44],"each":[45],"induces":[47],"feedback":[48],"over":[49],"candidate":[50,81],"experts,":[51],"committee's":[54],"value":[55],"on":[56],"is":[59,94,149,162],"determined":[60],"by":[61,85],"its":[62],"best-performing":[63],"member.":[64],"analyze":[66],"both":[67],"binary":[68,89],"feedback,":[69,77],"for":[70,78],"with":[72],"correct/incorrect":[73],"outcomes,":[74],"pairwise":[76,126,171],"where":[80],"outputs":[82],"compared":[84],"preference.":[86],"In":[87,124],"the":[88,91,115,125,147,196,201],"setting,":[90,127],"induced":[92],"objective":[93,148],"coverage.":[95],"give":[97],"exhaustive-elicitation":[98],"baselines":[99],"matching":[101],"worst-case":[102],"query":[103,122,198],"lower":[104],"bounds,":[105],"we":[107,128],"design":[108],"failure-conditioned":[110,167],"greedy":[111,168],"algorithm":[112],"that":[113,134,146],"preserves":[114],"standard":[116],"$(1-1/e)$":[117],"guarantee":[118],"while":[119],"obtaining":[120],"instance-dependent":[121],"savings.":[123],"$\u03b8$-winning":[130],"committees.":[131],"show":[133],"full-information":[135],"optimization":[136],"admits":[137],"PTAS":[139],"no":[141],"EPTAS":[142],"under":[143,170],"Gap-ETH,":[144],"monotone":[150],"not":[152],"submodular.":[153],"This":[154],"motivates":[155],"weighted":[157],"ordinal":[158],"coverage":[159],"relaxation,":[160],"which":[161],"submodular":[163],"supports":[165],"oracle":[169,177],"feedback.":[172],"then":[174],"convert":[175],"back":[178],"into":[179],"$\u03b8$-type":[180],"guarantees":[181],"through":[182],"finite-family":[183],"auditing":[184],"or":[185],"minimax":[187],"wrapper.":[188],"also":[190],"provide":[191],"small-scale":[192],"LLM":[193],"experiments":[194],"illustrating":[195],"predicted":[197],"savings":[199],"role":[202],"complementarity":[204],"in":[205],"committee":[206],"selection.":[207]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-05-13T00:00:00"}