{"id":"https://openalex.org/W4389667772","doi":"https://doi.org/10.1109/iros55552.2023.10342081","title":"Optimizing Algorithms from Pairwise User Preferences","display_name":"Optimizing Algorithms from Pairwise User Preferences","publication_year":2023,"publication_date":"2023-10-01","ids":{"openalex":"https://openalex.org/W4389667772","doi":"https://doi.org/10.1109/iros55552.2023.10342081"},"language":"en","primary_location":{"id":"doi:10.1109/iros55552.2023.10342081","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros55552.2023.10342081","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5090078593","display_name":"Leonid Keselman","orcid":null},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Leonid Keselman","raw_affiliation_strings":["Robotics Institute, School of Computer Science, Carnegie Mellon University,Pittsburgh,PA,USA,15232"],"affiliations":[{"raw_affiliation_string":"Robotics Institute, School of Computer Science, Carnegie Mellon University,Pittsburgh,PA,USA,15232","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003631475","display_name":"Katherine Shih","orcid":"https://orcid.org/0009-0007-8666-0171"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Katherine Shih","raw_affiliation_strings":["Robotics Institute, School of Computer Science, Carnegie Mellon University,Pittsburgh,PA,USA,15232"],"affiliations":[{"raw_affiliation_string":"Robotics Institute, School of Computer Science, Carnegie Mellon University,Pittsburgh,PA,USA,15232","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075246991","display_name":"Martial Hebert","orcid":"https://orcid.org/0000-0003-4566-5930"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Martial Hebert","raw_affiliation_strings":["Robotics Institute, School of Computer Science, Carnegie Mellon University,Pittsburgh,PA,USA,15232"],"affiliations":[{"raw_affiliation_string":"Robotics Institute, School of Computer Science, Carnegie Mellon University,Pittsburgh,PA,USA,15232","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108044002","display_name":"Aaron Steinfeld","orcid":"https://orcid.org/0000-0003-2274-0053"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Aaron Steinfeld","raw_affiliation_strings":["Robotics Institute, School of Computer Science, Carnegie Mellon University,Pittsburgh,PA,USA,15232"],"affiliations":[{"raw_affiliation_string":"Robotics Institute, School of Computer Science, Carnegie Mellon University,Pittsburgh,PA,USA,15232","institution_ids":["https://openalex.org/I74973139"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5090078593"],"corresponding_institution_ids":["https://openalex.org/I74973139"],"apc_list":null,"apc_paid":null,"fwci":1.0426,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.82067844,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"4161","last_page":"4167"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9997000098228455,"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9997000098228455,"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/T10586","display_name":"Robotic Path Planning Algorithms","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.7847082614898682},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.7699425220489502},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7497403621673584},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.6480172872543335},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.6219921112060547},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5759581327438354},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.573982298374176},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.5167383551597595},{"id":"https://openalex.org/keywords/robotics","display_name":"Robotics","score":0.45752251148223877},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.45421895384788513},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.4225071966648102}],"concepts":[{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.7847082614898682},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7699425220489502},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7497403621673584},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.6480172872543335},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.6219921112060547},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5759581327438354},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.573982298374176},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.5167383551597595},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.45752251148223877},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.45421895384788513},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4225071966648102},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iros55552.2023.10342081","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros55552.2023.10342081","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1281144321","display_name":null,"funder_award_id":"90DPGE0003","funder_id":"https://openalex.org/F4320337345","funder_display_name":"Office of Naval Research"},{"id":"https://openalex.org/G5102661972","display_name":null,"funder_award_id":"90DPGE0003","funder_id":"https://openalex.org/F4320337112","funder_display_name":"National Institute on Disability and Rehabilitation Research"}],"funders":[{"id":"https://openalex.org/F4320337112","display_name":"National Institute on Disability and Rehabilitation Research","ror":"https://ror.org/021adze67"},{"id":"https://openalex.org/F4320337345","display_name":"Office of Naval Research","ror":"https://ror.org/00rk2pe57"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W63091017","https://openalex.org/W102487131","https://openalex.org/W1583837637","https://openalex.org/W1965520710","https://openalex.org/W1970206276","https://openalex.org/W1999874108","https://openalex.org/W2038435918","https://openalex.org/W2039251018","https://openalex.org/W2117248802","https://openalex.org/W2119401655","https://openalex.org/W2137591261","https://openalex.org/W2148961728","https://openalex.org/W2314046539","https://openalex.org/W2474958793","https://openalex.org/W2532516272","https://openalex.org/W2604382266","https://openalex.org/W2700163520","https://openalex.org/W2745471877","https://openalex.org/W2799745602","https://openalex.org/W3011144947","https://openalex.org/W3039563104","https://openalex.org/W3093708494","https://openalex.org/W3134000433","https://openalex.org/W3134972302","https://openalex.org/W3187304456","https://openalex.org/W3196191018","https://openalex.org/W3203930968","https://openalex.org/W3206750208","https://openalex.org/W3212848654","https://openalex.org/W4206101546","https://openalex.org/W4211049957","https://openalex.org/W4221159071","https://openalex.org/W4223453348","https://openalex.org/W4252647407","https://openalex.org/W4285162787","https://openalex.org/W4293693810","https://openalex.org/W4323650814","https://openalex.org/W4376891303","https://openalex.org/W4383097429","https://openalex.org/W6680821758","https://openalex.org/W6739174935","https://openalex.org/W6784106160","https://openalex.org/W6809871608"],"related_works":["https://openalex.org/W2487162673","https://openalex.org/W2793211469","https://openalex.org/W2949152769","https://openalex.org/W4372354731","https://openalex.org/W2942366970","https://openalex.org/W2807634898","https://openalex.org/W1692008701","https://openalex.org/W2597588799","https://openalex.org/W4360593462","https://openalex.org/W2894446834"],"abstract_inverted_index":{"Typical":[0],"black-box":[1],"optimization":[2],"approaches":[3,45],"in":[4,30,49,80,136],"robotics":[5],"focus":[6],"on":[7,84],"learning":[8],"from":[9],"metric":[10,42],"scores.":[11,43],"However,":[12],"that":[13,132],"is":[14],"not":[15,19],"always":[16],"possible,":[17],"as":[18],"all":[20],"developers":[21],"have":[22],"ground":[23,115],"truth":[24],"available.":[25],"Learning":[26],"appropriate":[27],"robot":[28,119,128],"behavior":[29],"human-centric":[31],"contexts":[32],"often":[33],"requires":[34],"querying":[35],"users,":[36],"who":[37],"typically":[38],"cannot":[39],"provide":[40],"precise":[41],"Existing":[44],"leverage":[46],"human":[47],"feedback":[48],"an":[50,54],"attempt":[51],"to":[52,66,75,95,108,118,147],"model":[53],"implicit":[55],"reward":[56,60],"function;":[57],"however,":[58],"this":[59,70,106],"may":[61],"be":[62],"difficult":[63],"or":[64],"impossible":[65],"effectively":[67],"capture.":[68],"In":[69],"work,":[71],"we":[72],"introduce":[73],"SortCMA":[74,88],"optimize":[76],"algorithm":[77],"parameter":[78,97],"configurations":[79],"high":[81],"dimensions":[82],"based":[83],"pairwise":[85],"user":[86,93,145],"preferences.":[87],"efficiently":[89],"and":[90,117,142],"robustly":[91],"leverages":[92],"input":[94],"find":[96],"sets":[98],"without":[99,114],"directly":[100],"modeling":[101],"a":[102,110,144],"reward.":[103],"We":[104,130],"apply":[105],"method":[107,134],"tuning":[109],"commercial":[111],"depth":[112],"sensor":[113],"truth,":[116],"social":[120,149],"navigation,":[121],"which":[122],"involves":[123],"highly":[124],"complex":[125],"preferences":[126],"over":[127],"behavior.":[129],"show":[131],"our":[133],"succeeds":[135],"optimizing":[137],"for":[138],"the":[139],"user's":[140],"goals":[141],"perform":[143],"study":[146],"evaluate":[148],"navigation":[150],"results.":[151]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2}],"updated_date":"2026-03-31T07:56:22.981413","created_date":"2025-10-10T00:00:00"}
