{"id":"https://openalex.org/W4382365142","doi":"https://doi.org/10.1109/itw55543.2023.10161673","title":"Permutation Invariant Individual Batch Learning","display_name":"Permutation Invariant Individual Batch Learning","publication_year":2023,"publication_date":"2023-04-23","ids":{"openalex":"https://openalex.org/W4382365142","doi":"https://doi.org/10.1109/itw55543.2023.10161673"},"language":"en","primary_location":{"id":"doi:10.1109/itw55543.2023.10161673","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/itw55543.2023.10161673","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE Information Theory Workshop (ITW)","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/A5005484384","display_name":"Yaniv Fogel","orcid":null},"institutions":[{"id":"https://openalex.org/I16391192","display_name":"Tel Aviv University","ror":"https://ror.org/04mhzgx49","country_code":"IL","type":"education","lineage":["https://openalex.org/I16391192"]}],"countries":["IL"],"is_corresponding":true,"raw_author_name":"Yaniv Fogel","raw_affiliation_strings":["Tel Aviv University,School of Electrical Engineering","School of Electrical Engineering, Tel Aviv University"],"affiliations":[{"raw_affiliation_string":"Tel Aviv University,School of Electrical Engineering","institution_ids":["https://openalex.org/I16391192"]},{"raw_affiliation_string":"School of Electrical Engineering, Tel Aviv University","institution_ids":["https://openalex.org/I16391192"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066905280","display_name":"Meir Feder","orcid":"https://orcid.org/0000-0002-1290-0482"},"institutions":[{"id":"https://openalex.org/I16391192","display_name":"Tel Aviv University","ror":"https://ror.org/04mhzgx49","country_code":"IL","type":"education","lineage":["https://openalex.org/I16391192"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Meir Feder","raw_affiliation_strings":["Tel Aviv University,School of Electrical Engineering","School of Electrical Engineering, Tel Aviv University"],"affiliations":[{"raw_affiliation_string":"Tel Aviv University,School of Electrical Engineering","institution_ids":["https://openalex.org/I16391192"]},{"raw_affiliation_string":"School of Electrical Engineering, Tel Aviv University","institution_ids":["https://openalex.org/I16391192"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5005484384"],"corresponding_institution_ids":["https://openalex.org/I16391192"],"apc_list":null,"apc_paid":null,"fwci":0.1751,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.53527055,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"134","issue":null,"first_page":"142","last_page":"146"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":1.0,"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/T12072","display_name":"Machine Learning and Algorithms","score":1.0,"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":0.9990000128746033,"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/T12288","display_name":"Optimization and Search Problems","score":0.9904000163078308,"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/regret","display_name":"Regret","score":0.8513003587722778},{"id":"https://openalex.org/keywords/bernoullis-principle","display_name":"Bernoulli's principle","score":0.6852809190750122},{"id":"https://openalex.org/keywords/permutation","display_name":"Permutation (music)","score":0.6736895442008972},{"id":"https://openalex.org/keywords/invariant","display_name":"Invariant (physics)","score":0.5522022843360901},{"id":"https://openalex.org/keywords/outcome","display_name":"Outcome (game theory)","score":0.5314967036247253},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5260493755340576},{"id":"https://openalex.org/keywords/constant","display_name":"Constant (computer programming)","score":0.49164897203445435},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4355345666408539},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.43490540981292725},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.43422698974609375},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3731284737586975},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3435922861099243},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3143594264984131},{"id":"https://openalex.org/keywords/mathematical-economics","display_name":"Mathematical economics","score":0.09379124641418457}],"concepts":[{"id":"https://openalex.org/C50817715","wikidata":"https://www.wikidata.org/wiki/Q79895177","display_name":"Regret","level":2,"score":0.8513003587722778},{"id":"https://openalex.org/C152361515","wikidata":"https://www.wikidata.org/wiki/Q181328","display_name":"Bernoulli's principle","level":2,"score":0.6852809190750122},{"id":"https://openalex.org/C21308566","wikidata":"https://www.wikidata.org/wiki/Q7169365","display_name":"Permutation (music)","level":2,"score":0.6736895442008972},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.5522022843360901},{"id":"https://openalex.org/C148220186","wikidata":"https://www.wikidata.org/wiki/Q7111912","display_name":"Outcome (game theory)","level":2,"score":0.5314967036247253},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5260493755340576},{"id":"https://openalex.org/C2777027219","wikidata":"https://www.wikidata.org/wiki/Q1284190","display_name":"Constant (computer programming)","level":2,"score":0.49164897203445435},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4355345666408539},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.43490540981292725},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.43422698974609375},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3731284737586975},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3435922861099243},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3143594264984131},{"id":"https://openalex.org/C144237770","wikidata":"https://www.wikidata.org/wiki/Q747534","display_name":"Mathematical economics","level":1,"score":0.09379124641418457},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C37914503","wikidata":"https://www.wikidata.org/wiki/Q156495","display_name":"Mathematical physics","level":1,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/itw55543.2023.10161673","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/itw55543.2023.10161673","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE Information Theory Workshop (ITW)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1975551153","https://openalex.org/W1999120268","https://openalex.org/W2066688546","https://openalex.org/W2098397165","https://openalex.org/W2125232050","https://openalex.org/W2132119275","https://openalex.org/W2148574462","https://openalex.org/W2294584261","https://openalex.org/W2742781314","https://openalex.org/W2886419155","https://openalex.org/W2905701627","https://openalex.org/W2975162820","https://openalex.org/W3123545922","https://openalex.org/W3174504784","https://openalex.org/W4287365005","https://openalex.org/W4289655250","https://openalex.org/W6757735113","https://openalex.org/W6790465512"],"related_works":["https://openalex.org/W2971351794","https://openalex.org/W4376155396","https://openalex.org/W1947085858","https://openalex.org/W2101991911","https://openalex.org/W2174986909","https://openalex.org/W2527791220","https://openalex.org/W2155070487","https://openalex.org/W4311589891","https://openalex.org/W2377003726","https://openalex.org/W2065691918"],"abstract_inverted_index":{"This":[0,50,99],"paper":[1],"considers":[2],"the":[3,16,27,39,42,86,96,107,117,123,134,152,158,161,168,174,179,182,185,194],"individual":[4,52,87,195],"batch":[5,51],"learning":[6,9,36],"problem.":[7],"Batch":[8],"(in":[10],"contrast":[11],"to":[12,15,30,38],"online)":[13],"refers":[14,37],"case":[17,40,170],"where":[18,41,106],"there":[19,71],"is":[20,29,47,72,101,109],"a":[21,32,55,60,64,73,79,103,112,199],"\"batch\"":[22],"of":[23,58,160],"training":[24,88,162],"data":[25,43],"and":[26,45,120,136,145,163,171],"goal":[28],"predict":[31],"test":[33,75,97],"outcome.":[34],"Individual":[35],"(training":[44],"test)":[46],"arbitrary,":[48],"individual.":[49],"setting":[53,187],"poses":[54],"fundamental":[56],"issue":[57],"defining":[59],"plausible":[61],"criterion":[62,82,100,135],"for":[63,94,140,167,173],"universal":[65,118],"learner":[66,119,139],"since":[67],"in":[68,178,184,193],"each":[69],"experiment":[70],"single":[74],"sample.":[76,98],"We":[77],"propose":[78],"permutation":[80],"invariant":[81],"that,":[83],"intuitively,":[84],"lets":[85],"sequence":[89],"manifest":[90],"its":[91,130,137],"empirical":[92],"structure":[93],"predicting":[95],"essentially":[102],"min-max":[104],"regret,":[105],"regret":[108,153,183],"based":[110],"on":[111],"leave-one-out":[113],"approach,":[114],"minimized":[115],"over":[116,122],"maximized":[121],"outcome":[124],"sequences":[125],"(thus":[126],"agnostic).":[127],"To":[128],"show":[129],"plausibility,":[131],"we":[132],"analyze":[133],"resulting":[138],"two":[141],"cases:":[142],"Binary":[143],"Bernoulli":[144,169,180],"1-D":[146,175],"deterministic":[147],"barrier.":[148,176],"For":[149],"both":[150],"cases":[151],"behaves":[154,188],"as":[155,189],"O(c/N),":[156],"N":[157],"size":[159],"c":[164],"=":[165],"1":[166],"log4":[172],"Interestingly,":[177],"case,":[181],"stochastic":[186],"O(1/2N)":[190],"while":[191],"here,":[192],"setting,":[196],"it":[197],"has":[198],"larger":[200],"constant.":[201]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2025-12-21T01:58:51.020947","created_date":"2025-10-10T00:00:00"}
