{"id":"https://openalex.org/W4399522310","doi":"https://doi.org/10.1145/3618260.3649631","title":"Optimization with Pattern-Avoiding Input","display_name":"Optimization with Pattern-Avoiding Input","publication_year":2024,"publication_date":"2024-06-10","ids":{"openalex":"https://openalex.org/W4399522310","doi":"https://doi.org/10.1145/3618260.3649631"},"language":"en","primary_location":{"id":"doi:10.1145/3618260.3649631","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3618260.3649631","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3618260.3649631","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 56th Annual ACM Symposium on Theory of Computing","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3618260.3649631","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5065566770","display_name":"Benjamin Aram Berendsohn","orcid":"https://orcid.org/0000-0002-3430-5262"},"institutions":[{"id":"https://openalex.org/I75951250","display_name":"Freie Universit\u00e4t Berlin","ror":"https://ror.org/046ak2485","country_code":"DE","type":"education","lineage":["https://openalex.org/I75951250"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Benjamin Aram Berendsohn","raw_affiliation_strings":["Freie Universit\u00e4t Berlin, Berlin, Germany"],"affiliations":[{"raw_affiliation_string":"Freie Universit\u00e4t Berlin, Berlin, Germany","institution_ids":["https://openalex.org/I75951250"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065214797","display_name":"L\u00e1szl\u00f3 Kozma","orcid":"https://orcid.org/0000-0002-3253-2373"},"institutions":[{"id":"https://openalex.org/I75951250","display_name":"Freie Universit\u00e4t Berlin","ror":"https://ror.org/046ak2485","country_code":"DE","type":"education","lineage":["https://openalex.org/I75951250"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"L\u00e1szl\u00f3 Kozma","raw_affiliation_strings":["Freie Universit\u00e4t Berlin, Berlin, Germany"],"affiliations":[{"raw_affiliation_string":"Freie Universit\u00e4t Berlin, Berlin, Germany","institution_ids":["https://openalex.org/I75951250"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006649123","display_name":"Michal Opler","orcid":"https://orcid.org/0000-0002-4389-5807"},"institutions":[{"id":"https://openalex.org/I44504214","display_name":"Czech Technical University in Prague","ror":"https://ror.org/03kqpb082","country_code":"CZ","type":"education","lineage":["https://openalex.org/I44504214"]}],"countries":["CZ"],"is_corresponding":false,"raw_author_name":"Michal Opler","raw_affiliation_strings":["Czech Technical University, Prague, Czechia"],"affiliations":[{"raw_affiliation_string":"Czech Technical University, Prague, Czechia","institution_ids":["https://openalex.org/I44504214"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5065566770"],"corresponding_institution_ids":["https://openalex.org/I75951250"],"apc_list":null,"apc_paid":null,"fwci":0.3755,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.57816248,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"671","last_page":"682"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12288","display_name":"Optimization and Search Problems","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T12288","display_name":"Optimization and Search Problems","score":1.0,"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"}},{"id":"https://openalex.org/T11269","display_name":"Algorithms and Data Compression","score":0.9922000169754028,"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/T10720","display_name":"Complexity and Algorithms in Graphs","score":0.9912999868392944,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/combinatorics","display_name":"Combinatorics","score":0.796323299407959},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.7229214906692505},{"id":"https://openalex.org/keywords/ackermann-function","display_name":"Ackermann function","score":0.6564890146255493},{"id":"https://openalex.org/keywords/conjecture","display_name":"Conjecture","score":0.5681057572364807},{"id":"https://openalex.org/keywords/upper-and-lower-bounds","display_name":"Upper and lower bounds","score":0.4924484193325043},{"id":"https://openalex.org/keywords/permutation","display_name":"Permutation (music)","score":0.4650574326515198},{"id":"https://openalex.org/keywords/amortized-analysis","display_name":"Amortized analysis","score":0.4568745195865631},{"id":"https://openalex.org/keywords/inverse","display_name":"Inverse","score":0.4264475703239441},{"id":"https://openalex.org/keywords/travelling-salesman-problem","display_name":"Travelling salesman problem","score":0.41447943449020386},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.4053894281387329},{"id":"https://openalex.org/keywords/data-structure","display_name":"Data structure","score":0.286309152841568},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2145920693874359},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.19999802112579346}],"concepts":[{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.796323299407959},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.7229214906692505},{"id":"https://openalex.org/C33436860","wikidata":"https://www.wikidata.org/wiki/Q341835","display_name":"Ackermann function","level":3,"score":0.6564890146255493},{"id":"https://openalex.org/C2780990831","wikidata":"https://www.wikidata.org/wiki/Q319141","display_name":"Conjecture","level":2,"score":0.5681057572364807},{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.4924484193325043},{"id":"https://openalex.org/C21308566","wikidata":"https://www.wikidata.org/wiki/Q7169365","display_name":"Permutation (music)","level":2,"score":0.4650574326515198},{"id":"https://openalex.org/C142417499","wikidata":"https://www.wikidata.org/wiki/Q331716","display_name":"Amortized analysis","level":3,"score":0.4568745195865631},{"id":"https://openalex.org/C207467116","wikidata":"https://www.wikidata.org/wiki/Q4385666","display_name":"Inverse","level":2,"score":0.4264475703239441},{"id":"https://openalex.org/C175859090","wikidata":"https://www.wikidata.org/wiki/Q322212","display_name":"Travelling salesman problem","level":2,"score":0.41447943449020386},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.4053894281387329},{"id":"https://openalex.org/C162319229","wikidata":"https://www.wikidata.org/wiki/Q175263","display_name":"Data structure","level":2,"score":0.286309152841568},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2145920693874359},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.19999802112579346},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3618260.3649631","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3618260.3649631","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3618260.3649631","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 56th Annual ACM Symposium on Theory of Computing","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3618260.3649631","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3618260.3649631","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3618260.3649631","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 56th Annual ACM Symposium on Theory of Computing","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4399522310.pdf"},"referenced_works_count":51,"referenced_works":["https://openalex.org/W166539567","https://openalex.org/W758484163","https://openalex.org/W1515964912","https://openalex.org/W1521561776","https://openalex.org/W1552828154","https://openalex.org/W1624114741","https://openalex.org/W1747890423","https://openalex.org/W1956214747","https://openalex.org/W1993875587","https://openalex.org/W1996406174","https://openalex.org/W2014068360","https://openalex.org/W2016857845","https://openalex.org/W2017619076","https://openalex.org/W2037022974","https://openalex.org/W2052359455","https://openalex.org/W2070091651","https://openalex.org/W2078913074","https://openalex.org/W2082099352","https://openalex.org/W2083354900","https://openalex.org/W2086989193","https://openalex.org/W2091015960","https://openalex.org/W2091505308","https://openalex.org/W2100311357","https://openalex.org/W2130055503","https://openalex.org/W2133320102","https://openalex.org/W2134026356","https://openalex.org/W2397978869","https://openalex.org/W2558067245","https://openalex.org/W2752061190","https://openalex.org/W2888882694","https://openalex.org/W2892208052","https://openalex.org/W2909747729","https://openalex.org/W2950143318","https://openalex.org/W2963787010","https://openalex.org/W2966027757","https://openalex.org/W2983155364","https://openalex.org/W3133527322","https://openalex.org/W3137830407","https://openalex.org/W3186106518","https://openalex.org/W3188548511","https://openalex.org/W3195126852","https://openalex.org/W3205561455","https://openalex.org/W3216575656","https://openalex.org/W4241180678","https://openalex.org/W4242724277","https://openalex.org/W4254465499","https://openalex.org/W4255385822","https://openalex.org/W4316652367","https://openalex.org/W4390575932","https://openalex.org/W4390575957","https://openalex.org/W6631301451"],"related_works":["https://openalex.org/W2076743759","https://openalex.org/W4235144492","https://openalex.org/W4388435768","https://openalex.org/W2756792282","https://openalex.org/W2756744637","https://openalex.org/W2759493398","https://openalex.org/W3216309640","https://openalex.org/W2807877113","https://openalex.org/W4247734921","https://openalex.org/W4237598456"],"abstract_inverted_index":{"Permutation":[0],"pattern-avoidance":[1,21],"is":[2,61,67,75,88,148],"a":[3,105,111,149,174,183,190,206,214],"central":[4],"concept":[5,264],"of":[6,19,25,31,54,145,186,210,217,255,265],"both":[7,243],"enumerative":[8],"and":[9,44,82,92,204,238,259],"extremal":[10],"combinatorics.":[11],"In":[12,28,97],"this":[13,98,128],"paper":[14,99],"we":[15,100,140,164],"study":[16],"the":[17,23,29,32,50,64,89,94,102,143,168,200,223,231,252,256,261],"effect":[18],"permutation":[20],"on":[22,251,260],"complexity":[24],"optimization":[26],"problems.":[27],"context":[30],"dynamic":[33,114],"optimality":[34],"conjecture":[35],"(Sleator,":[36],"Tarjan,":[37],"STOC":[38],"1983),":[39],"Chalermsook,":[40,80],"Goswami,":[41],"Kozma,":[42],"Mehlhorn,":[43],"Saranurak":[45],"(FOCS":[46],"2015)":[47],"conjectured":[48],"that":[49,142,166],"amortized":[51],"search":[52,58,65],"cost":[53,195],"an":[55,171],"optimal":[56],"binary":[57],"tree":[59],"(BST)":[60],"constant":[62],"whenever":[63],"sequence":[66],"pattern-avoiding.":[68],"The":[69],"best":[70],"known":[71],"bound":[72],"to":[73,113,154,158,199,222,245],"date":[74],"2\u03b1(n)(1+o(1))":[76],"recently":[77,262],"obtained":[78],"by":[79],"Pettie,":[81],"Yingchareonthawornchai":[83],"(SODA":[84],"2024);":[85],"here":[86],"n":[87,187,211],"BST":[90,119],"size":[91],"\u03b1(\u00b7)":[93],"inverse-Ackermann":[95],"function.":[96],"resolve":[101],"conjecture,":[103,258],"showing":[104],"tight":[106],"(1)":[107,182],"bound.":[108],"This":[109],"indicates":[110],"barrier":[112],"optimality:":[115],"any":[116],"candidate":[117],"online":[118],"(e.g.,":[120],"splay":[121],"trees":[122],"or":[123,156],"greedy":[124],"trees)":[125],"must":[126],"match":[127],"optimum,":[129],"but":[130],"current":[131],"analysis":[132],"techniques":[133,249],"only":[134],"give":[135],"superconstant":[136],"bounds.":[137],"More":[138],"broadly,":[139],"argue":[141],"easiness":[144],"pattern-avoiding":[146],"input":[147,169],"general":[150],"phenomenon,":[151],"not":[152],"limited":[153],"BSTs":[155],"even":[157],"data":[159],"structures.":[160],"To":[161],"illustrate":[162],"this,":[163],"show":[165,242],"when":[167],"avoids":[170],"arbitrary,":[172],"fixed,":[173],"priori":[175],"unknown":[176],"pattern,":[177],"one":[178],"can":[179],"efficiently":[180],"compute:":[181],"k-server":[184],"solution":[185],"requests":[188],"from":[189,213],"unit":[191,215],"interval,":[192],"with":[193],"total":[194],"n(1/logk),":[196],"in":[197,220],"contrast":[198,221],"worst-case":[201,224],"\u0398(n/k)":[202],"bound,":[203],"(2)":[205],"traveling":[207],"salesman":[208],"tour":[209],"points":[212],"box,":[216],"length":[218],"(logn),":[219],"\u0398(\u221an)":[225],"bound;":[226],"similar":[227],"results":[228,244],"hold":[229],"for":[230],"euclidean":[232],"minimum":[233],"spanning":[234],"tree,":[235,237],"Steiner":[236],"nearest-neighbor":[239],"graphs.":[240],"We":[241],"be":[246],"tight.":[247],"Our":[248],"build":[250],"Marcus-Tardos":[253],"proof":[254],"Stanley-Wilf":[257],"emerging":[263],"twin-width.":[266]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
