{"id":"https://openalex.org/W7163166771","doi":"https://doi.org/10.48550/arxiv.2606.00366","title":"GLENS: Global Search via Learning from Solver Iterates with Diffusion Models","display_name":"GLENS: Global Search via Learning from Solver Iterates with Diffusion Models","publication_year":2026,"publication_date":"2026-05-29","ids":{"openalex":"https://openalex.org/W7163166771","doi":"https://doi.org/10.48550/arxiv.2606.00366"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.00366","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.00366","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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.2606.00366","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5137640774","display_name":"Anjian Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Anjian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081461094","display_name":"Bartolomeo Stellato","orcid":"https://orcid.org/0000-0003-4684-7111"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Stellato, Bartolomeo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5135967714","display_name":"Ryne Beeson","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Beeson, Ryne","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/T10963","display_name":"Advanced Optimization Algorithms Research","score":0.18310000002384186,"subfield":{"id":"https://openalex.org/subfields/2612","display_name":"Numerical Analysis"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10963","display_name":"Advanced Optimization Algorithms Research","score":0.18310000002384186,"subfield":{"id":"https://openalex.org/subfields/2612","display_name":"Numerical Analysis"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.12999999523162842,"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/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.07479999959468842,"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/solver","display_name":"Solver","score":0.8788999915122986},{"id":"https://openalex.org/keywords/local-optimum","display_name":"Local optimum","score":0.7498999834060669},{"id":"https://openalex.org/keywords/maxima-and-minima","display_name":"Maxima and minima","score":0.7103999853134155},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.607699990272522},{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.6068000197410583},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5946000218391418},{"id":"https://openalex.org/keywords/iterated-local-search","display_name":"Iterated local search","score":0.541100025177002}],"concepts":[{"id":"https://openalex.org/C2778770139","wikidata":"https://www.wikidata.org/wiki/Q1966904","display_name":"Solver","level":2,"score":0.8788999915122986},{"id":"https://openalex.org/C141934464","wikidata":"https://www.wikidata.org/wiki/Q3305386","display_name":"Local optimum","level":2,"score":0.7498999834060669},{"id":"https://openalex.org/C186633575","wikidata":"https://www.wikidata.org/wiki/Q845060","display_name":"Maxima and minima","level":2,"score":0.7103999853134155},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.607699990272522},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.6068000197410583},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.6014000177383423},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5946000218391418},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5892999768257141},{"id":"https://openalex.org/C124145224","wikidata":"https://www.wikidata.org/wiki/Q6094397","display_name":"Iterated local search","level":3,"score":0.541100025177002},{"id":"https://openalex.org/C135320971","wikidata":"https://www.wikidata.org/wiki/Q1868524","display_name":"Local search (optimization)","level":2,"score":0.5297999978065491},{"id":"https://openalex.org/C140479938","wikidata":"https://www.wikidata.org/wiki/Q5254619","display_name":"Iterated function","level":2,"score":0.4846000075340271},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4652999937534332},{"id":"https://openalex.org/C57869625","wikidata":"https://www.wikidata.org/wiki/Q1783502","display_name":"Rate of convergence","level":3,"score":0.3310000002384186},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.32739999890327454},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.3246999979019165},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3061000108718872},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.30239999294281006},{"id":"https://openalex.org/C3019612716","wikidata":"https://www.wikidata.org/wiki/Q730920","display_name":"Problem solver","level":2,"score":0.2847999930381775},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.25679999589920044},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.25029999017715454}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.00366","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.00366","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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.2606.00366","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.00366","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":[{"score":0.6620137691497803,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"We":[0,91,201],"consider":[1],"the":[2,68,80,87,130,179,209],"problem":[3,137,169,197],"of":[4,9,15,83,117,182],"generating":[5],"a":[6,32,101,120,140,165],"large":[7],"collection":[8],"initial":[10,26,64,175,188],"guesses":[11,27,65,176,189],"for":[12,24],"local":[13,43,81,131,184],"minima":[14],"multimodal":[16,180],"non-convex":[17,161],"continuous":[18],"optimization":[19],"problems.":[20],"The":[21,186],"goal":[22],"is":[23],"these":[25],"to":[28,128,148,191],"be":[29],"high-quality":[30,174],"(i.e.,":[31,39],"numerical":[33],"solver":[34,74,109,141,193],"converges":[35],"quickly)":[36],"and":[37,85,139,164,199],"diverse":[38,183],"represent":[40],"many":[41],"different":[42,196],"minima).":[44],"Identifying":[45],"multiple":[46],"locally":[47],"optimal":[48],"solutions":[49,84],"enables":[50],"flexible":[51],"downstream":[52],"decision-making,":[53],"but":[54],"typically":[55],"requires":[56],"expensive":[57],"global":[58,103],"search.":[59],"Existing":[60],"data-driven":[61],"methods":[62],"predict":[63],"using":[66],"only":[67],"final":[69],"converged":[70],"optima":[71,134,154],"from":[72,98],"offline":[73],"runs,":[75],"which":[76],"discards":[77],"information":[78],"about":[79],"neighborhoods":[82],"limits":[86],"available":[88],"training":[89],"data.":[90],"propose":[92],"GLENS":[93,115,172],"(Global":[94],"Search":[95],"via":[96],"Learning":[97],"Solver":[99],"Iterates),":[100],"data-efficient":[102],"search":[104],"method":[105],"that":[106,124,144,171],"leverages":[107],"intermediate":[108],"iterates":[110],"as":[111],"free":[112],"data":[113],"augmentation.":[114],"consists":[116],"two":[118],"components:":[119],"neighborhood":[121],"structure":[122],"model":[123,143],"uses":[125],"diffusion":[126,156],"models":[127],"learn":[129],"geometry":[132],"around":[133],"conditioned":[135],"on":[136,159],"parameters,":[138],"behavior":[142],"learns":[145],"refinement":[146],"directions":[147],"further":[149],"guide":[150],"samples":[151],"towards":[152],"nearby":[153],"during":[155],"sampling.":[157],"Experiments":[158],"modified":[160],"benchmark":[162],"problems":[163],"two-robot":[166],"obstacle-avoidance":[167],"navigation":[168],"show":[170],"generates":[173],"while":[177],"preserving":[178],"distribution":[181],"optima.":[185],"resulting":[187],"lead":[190],"faster":[192],"convergence":[194],"across":[195],"settings":[198],"solvers.":[200],"also":[202],"analyze":[203],"how":[204],"key":[205],"hyperparameter":[206],"choices":[207],"affect":[208],"performance.":[210]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-06-03T00:00:00"}