{"id":"https://openalex.org/W4414690762","doi":"https://doi.org/10.48550/arxiv.2507.16734","title":"Testing and estimation in orthosymmetric Gaussian sequence model","display_name":"Testing and estimation in orthosymmetric Gaussian sequence model","publication_year":2025,"publication_date":"2025-07-22","ids":{"openalex":"https://openalex.org/W4414690762","doi":"https://doi.org/10.48550/arxiv.2507.16734"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2507.16734","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2507.16734","pdf_url":"https://arxiv.org/pdf/2507.16734","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2507.16734","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5083230284","display_name":"Zeyu Jia","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Jia, Zeyu","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5031031216","display_name":"Yury Polyanskiy","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Polyanskiy, Yury","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5083230284"],"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.3684999942779541,"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.3684999942779541,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.6636000275611877},{"id":"https://openalex.org/keywords/bounded-function","display_name":"Bounded function","score":0.6013000011444092},{"id":"https://openalex.org/keywords/regular-polygon","display_name":"Regular polygon","score":0.5231999754905701},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.5059000253677368},{"id":"https://openalex.org/keywords/ellipsoid","display_name":"Ellipsoid","score":0.4722999930381775},{"id":"https://openalex.org/keywords/upper-and-lower-bounds","display_name":"Upper and lower bounds","score":0.4661000072956085},{"id":"https://openalex.org/keywords/quadratic-growth","display_name":"Quadratic growth","score":0.4099999964237213},{"id":"https://openalex.org/keywords/estimation-theory","display_name":"Estimation theory","score":0.4075999855995178},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.38679999113082886}],"concepts":[{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.746999979019165},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.6636000275611877},{"id":"https://openalex.org/C34388435","wikidata":"https://www.wikidata.org/wiki/Q2267362","display_name":"Bounded function","level":2,"score":0.6013000011444092},{"id":"https://openalex.org/C112680207","wikidata":"https://www.wikidata.org/wiki/Q714886","display_name":"Regular polygon","level":2,"score":0.5231999754905701},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5059000253677368},{"id":"https://openalex.org/C57489055","wikidata":"https://www.wikidata.org/wiki/Q190046","display_name":"Ellipsoid","level":2,"score":0.4722999930381775},{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.4661000072956085},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.43779999017715454},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4147999882698059},{"id":"https://openalex.org/C195956108","wikidata":"https://www.wikidata.org/wiki/Q7268362","display_name":"Quadratic growth","level":2,"score":0.4099999964237213},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.4075999855995178},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.38679999113082886},{"id":"https://openalex.org/C129848803","wikidata":"https://www.wikidata.org/wiki/Q2564360","display_name":"Sample size determination","level":2,"score":0.3767000138759613},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.35580000281333923},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3521000146865845},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.3490999937057495},{"id":"https://openalex.org/C87007009","wikidata":"https://www.wikidata.org/wiki/Q210832","display_name":"Statistical hypothesis testing","level":2,"score":0.3456000089645386},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.34549999237060547},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.33799999952316284},{"id":"https://openalex.org/C2778445095","wikidata":"https://www.wikidata.org/wiki/Q18354077","display_name":"Sample complexity","level":2,"score":0.3271999955177307},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.31279999017715454},{"id":"https://openalex.org/C49870271","wikidata":"https://www.wikidata.org/wiki/Q193657","display_name":"Convex set","level":4,"score":0.30079999566078186},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.3003000020980835},{"id":"https://openalex.org/C129844170","wikidata":"https://www.wikidata.org/wiki/Q41299","display_name":"Quadratic equation","level":2,"score":0.29840001463890076},{"id":"https://openalex.org/C2777299769","wikidata":"https://www.wikidata.org/wiki/Q3707858","display_name":"Type (biology)","level":2,"score":0.28139999508857727},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.27309998869895935},{"id":"https://openalex.org/C157972887","wikidata":"https://www.wikidata.org/wiki/Q463359","display_name":"Convex optimization","level":3,"score":0.262800008058548},{"id":"https://openalex.org/C183905921","wikidata":"https://www.wikidata.org/wiki/Q1038757","display_name":"Multiple comparisons problem","level":2,"score":0.25929999351501465}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2507.16734","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2507.16734","pdf_url":"https://arxiv.org/pdf/2507.16734","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2507.16734","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2507.16734","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2507.16734","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2507.16734","pdf_url":"https://arxiv.org/pdf/2507.16734","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"We":[0,23,64],"study":[1],"the":[2,34,37,81,90],"Gaussian":[3],"sequence":[4],"model,":[5],"i.e.":[6],"$X":[7],"\\sim":[8],"N(\\mathbf\u03b8,":[9],"I_\\infty)$,":[10],"where":[11],"$\\mathbf\u03b8":[12],"\\in":[13],"\u0393\\subset":[14],"\\ell_2$":[15],"is":[16,30,42,47,51],"assumed":[17],"to":[18,89],"be":[19],"convex":[20,54],"and":[21,85,100],"compact.":[22],"show":[24],"that":[25],"goodness-of-fit":[26],"testing":[27,70],"sample":[28],"complexity":[29,72],"lower":[31,45],"bounded":[32],"by":[33,57],"square-root":[35],"of":[36,78,83,92],"estimation":[38],"complexity,":[39],"whenever":[40],"$\u0393$":[41,50],"orthosymmetric.":[43],"This":[44],"bound":[46],"tight":[48],"when":[49],"also":[52,65],"quadratically":[53],"(as":[55],"shown":[56],"[Donoho":[58],"et":[59],"al.":[60],"1990,":[61],"Neykov":[62],"2023]).":[63],"completely":[66],"characterize":[67],"likelihood-free":[68],"hypothesis":[69],"(LFHT)":[71],"for":[73],"$\\ell_p$-bodies,":[74],"discovering":[75],"new":[76],"types":[77],"tradeoff":[79],"between":[80],"numbers":[82],"simulation":[84],"observation":[86],"samples,":[87],"compared":[88],"case":[91],"ellipsoids":[93],"(p":[94],"=":[95],"2)":[96],"studied":[97],"in":[98],"[Gerber":[99],"Polyanskiy":[101],"2024].":[102]},"counts_by_year":[],"updated_date":"2026-04-06T07:47:59.780226","created_date":"2025-10-10T00:00:00"}
