{"id":"https://openalex.org/W2152435742","doi":"https://doi.org/10.1007/s11222-015-9608-z","title":"Random projections for Bayesian regression","display_name":"Random projections for Bayesian regression","publication_year":2015,"publication_date":"2015-11-19","ids":{"openalex":"https://openalex.org/W2152435742","doi":"https://doi.org/10.1007/s11222-015-9608-z","mag":"2152435742"},"language":"en","primary_location":{"id":"doi:10.1007/s11222-015-9608-z","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11222-015-9608-z","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11222-015-9608-z.pdf","source":{"id":"https://openalex.org/S5437875","display_name":"Statistics and Computing","issn_l":"0960-3174","issn":["0960-3174","1573-1375"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Statistics and Computing","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s11222-015-9608-z.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5052502058","display_name":"Leo N. Geppert","orcid":null},"institutions":[{"id":"https://openalex.org/I200332995","display_name":"TU Dortmund University","ror":"https://ror.org/01k97gp34","country_code":"DE","type":"education","lineage":["https://openalex.org/I200332995"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Leo N. Geppert","raw_affiliation_strings":["Department of Statistics, Technische Universitt Dortmund, 44221 Dortmund, Germany","Department of Statistics, Technische Universit\u00e4t Dortmund, 44221, Dortmund, Germany"],"affiliations":[{"raw_affiliation_string":"Department of Statistics, Technische Universitt Dortmund, 44221 Dortmund, Germany","institution_ids":["https://openalex.org/I200332995"]},{"raw_affiliation_string":"Department of Statistics, Technische Universit\u00e4t Dortmund, 44221, Dortmund, Germany","institution_ids":["https://openalex.org/I200332995"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063815245","display_name":"Katja Ickstadt","orcid":"https://orcid.org/0000-0001-5157-2496"},"institutions":[{"id":"https://openalex.org/I200332995","display_name":"TU Dortmund University","ror":"https://ror.org/01k97gp34","country_code":"DE","type":"education","lineage":["https://openalex.org/I200332995"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Katja Ickstadt","raw_affiliation_strings":["Department of Statistics, Technische Universitt Dortmund, 44221 Dortmund, Germany","Department of Statistics, Technische Universit\u00e4t Dortmund, 44221, Dortmund, Germany"],"affiliations":[{"raw_affiliation_string":"Department of Statistics, Technische Universitt Dortmund, 44221 Dortmund, Germany","institution_ids":["https://openalex.org/I200332995"]},{"raw_affiliation_string":"Department of Statistics, Technische Universit\u00e4t Dortmund, 44221, Dortmund, Germany","institution_ids":["https://openalex.org/I200332995"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023613530","display_name":"Alexander Munteanu","orcid":"https://orcid.org/0000-0001-6549-3270"},"institutions":[{"id":"https://openalex.org/I200332995","display_name":"TU Dortmund University","ror":"https://ror.org/01k97gp34","country_code":"DE","type":"education","lineage":["https://openalex.org/I200332995"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Alexander Munteanu","raw_affiliation_strings":["Department of Computer Science, Technische Universitt Dortmund, 44221 Dortmund, Germany","Department of Computer Science, Technische Universit\u00e4t Dortmund, 44221, Dortmund, Germany"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Technische Universitt Dortmund, 44221 Dortmund, Germany","institution_ids":["https://openalex.org/I200332995"]},{"raw_affiliation_string":"Department of Computer Science, Technische Universit\u00e4t Dortmund, 44221, Dortmund, Germany","institution_ids":["https://openalex.org/I200332995"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066005269","display_name":"Jens Quedenfeld","orcid":"https://orcid.org/0000-0001-9690-0123"},"institutions":[{"id":"https://openalex.org/I200332995","display_name":"TU Dortmund University","ror":"https://ror.org/01k97gp34","country_code":"DE","type":"education","lineage":["https://openalex.org/I200332995"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Jens Quedenfeld","raw_affiliation_strings":["Department of Computer Science, Technische Universitt Dortmund, 44221 Dortmund, Germany","Department of Computer Science, Technische Universit\u00e4t Dortmund, 44221, Dortmund, Germany"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Technische Universitt Dortmund, 44221 Dortmund, Germany","institution_ids":["https://openalex.org/I200332995"]},{"raw_affiliation_string":"Department of Computer Science, Technische Universit\u00e4t Dortmund, 44221, Dortmund, Germany","institution_ids":["https://openalex.org/I200332995"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034247955","display_name":"Christian Sohler","orcid":"https://orcid.org/0000-0001-8990-3326"},"institutions":[{"id":"https://openalex.org/I200332995","display_name":"TU Dortmund University","ror":"https://ror.org/01k97gp34","country_code":"DE","type":"education","lineage":["https://openalex.org/I200332995"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Christian Sohler","raw_affiliation_strings":["Department of Computer Science, Technische Universitt Dortmund, 44221 Dortmund, Germany","Department of Computer Science, Technische Universit\u00e4t Dortmund, 44221, Dortmund, Germany"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Technische Universitt Dortmund, 44221 Dortmund, Germany","institution_ids":["https://openalex.org/I200332995"]},{"raw_affiliation_string":"Department of Computer Science, Technische Universit\u00e4t Dortmund, 44221, Dortmund, Germany","institution_ids":["https://openalex.org/I200332995"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5052502058"],"corresponding_institution_ids":["https://openalex.org/I200332995"],"apc_list":{"value":2090,"currency":"EUR","value_usd":2690},"apc_paid":{"value":2090,"currency":"EUR","value_usd":2690},"fwci":5.3605,"has_fulltext":true,"cited_by_count":39,"citation_normalized_percentile":{"value":0.95743745,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"27","issue":"1","first_page":"79","last_page":"101"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.998199999332428,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.998199999332428,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9943000078201294,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"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/T12056","display_name":"Markov Chains and Monte Carlo Methods","score":0.9934999942779541,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.7521287202835083},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.6863659620285034},{"id":"https://openalex.org/keywords/bayesian-linear-regression","display_name":"Bayesian linear regression","score":0.6295520067214966},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.6125149726867676},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.5219985246658325},{"id":"https://openalex.org/keywords/linear-regression","display_name":"Linear regression","score":0.4907892644405365},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.4898240268230438},{"id":"https://openalex.org/keywords/posterior-probability","display_name":"Posterior probability","score":0.46012163162231445},{"id":"https://openalex.org/keywords/bayesian-multivariate-linear-regression","display_name":"Bayesian multivariate linear regression","score":0.4563092291355133},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.42489778995513916},{"id":"https://openalex.org/keywords/distribution","display_name":"Distribution (mathematics)","score":0.41604459285736084},{"id":"https://openalex.org/keywords/beta-distribution","display_name":"Beta distribution","score":0.41100722551345825},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.33561450242996216},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3351787328720093},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.12171059846878052},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.0800582766532898}],"concepts":[{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.7521287202835083},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.6863659620285034},{"id":"https://openalex.org/C37903108","wikidata":"https://www.wikidata.org/wiki/Q4874474","display_name":"Bayesian linear regression","level":4,"score":0.6295520067214966},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.6125149726867676},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5219985246658325},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.4907892644405365},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.4898240268230438},{"id":"https://openalex.org/C57830394","wikidata":"https://www.wikidata.org/wiki/Q278079","display_name":"Posterior probability","level":3,"score":0.46012163162231445},{"id":"https://openalex.org/C64946054","wikidata":"https://www.wikidata.org/wiki/Q4874476","display_name":"Bayesian multivariate linear regression","level":3,"score":0.4563092291355133},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.42489778995513916},{"id":"https://openalex.org/C110121322","wikidata":"https://www.wikidata.org/wiki/Q865811","display_name":"Distribution (mathematics)","level":2,"score":0.41604459285736084},{"id":"https://openalex.org/C21621910","wikidata":"https://www.wikidata.org/wiki/Q756254","display_name":"Beta distribution","level":2,"score":0.41100722551345825},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.33561450242996216},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3351787328720093},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.12171059846878052},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0800582766532898},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1007/s11222-015-9608-z","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11222-015-9608-z","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11222-015-9608-z.pdf","source":{"id":"https://openalex.org/S5437875","display_name":"Statistics and Computing","issn_l":"0960-3174","issn":["0960-3174","1573-1375"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Statistics and Computing","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1504.06122","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1504.06122","pdf_url":"https://arxiv.org/pdf/1504.06122","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.650.5565","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.650.5565","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www-ai.cs.uni-dortmund.de/PublicPublicationFiles/geppert_etal_2014a.pdf","raw_type":"text"},{"id":"pmh:oai:eldorado.tu-dortmund.de:2003/37174","is_oa":false,"landing_page_url":"http://hdl.handle.net/2003/37174","pdf_url":null,"source":{"id":"https://openalex.org/S4377196631","display_name":"Eldorado - Repository of the TU Dortmund (TU Dortmund University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I200332995","host_organization_name":"TU Dortmund University","host_organization_lineage":["https://openalex.org/I200332995"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"doc-type:Text"},{"id":"doi:10.17877/de290r-19170","is_oa":true,"landing_page_url":"https://doi.org/10.17877/de290r-19170","pdf_url":null,"source":{"id":"https://openalex.org/S4306400811","display_name":"Technische Universit\u00e4t Dortmund Eldorado (Technische Universit\u00e4t Dortmund)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210148506","host_organization_name":"Erich-Brost-Institut","host_organization_lineage":["https://openalex.org/I4210148506"],"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":"report"}],"best_oa_location":{"id":"doi:10.1007/s11222-015-9608-z","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11222-015-9608-z","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11222-015-9608-z.pdf","source":{"id":"https://openalex.org/S5437875","display_name":"Statistics and Computing","issn_l":"0960-3174","issn":["0960-3174","1573-1375"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Statistics and Computing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5106512922","display_name":null,"funder_award_id":"Deutsche Forschungsgemeinschaft (DFG","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"},{"id":"https://openalex.org/G5523801029","display_name":null,"funder_award_id":"SFB 876","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"},{"id":"https://openalex.org/G6024419964","display_name":null,"funder_award_id":"Deutsche Forschungsgemeinschaft (DFG)","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"},{"id":"https://openalex.org/G6052429835","display_name":null,"funder_award_id":"(DFG)","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"},{"id":"https://openalex.org/G762232396","display_name":null,"funder_award_id":"Project","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"},{"id":"https://openalex.org/G8329488012","display_name":null,"funder_award_id":"SFB 876, C4","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"}],"funders":[{"id":"https://openalex.org/F4320320879","display_name":"Deutsche Forschungsgemeinschaft","ror":"https://ror.org/018mejw64"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2152435742.pdf","grobid_xml":"https://content.openalex.org/works/W2152435742.grobid-xml"},"referenced_works_count":90,"referenced_works":["https://openalex.org/W150179085","https://openalex.org/W385466589","https://openalex.org/W1480392687","https://openalex.org/W1506806321","https://openalex.org/W1536497620","https://openalex.org/W1554944419","https://openalex.org/W1601795611","https://openalex.org/W1624701674","https://openalex.org/W1663973292","https://openalex.org/W1809996565","https://openalex.org/W1859506250","https://openalex.org/W1960925516","https://openalex.org/W1965175390","https://openalex.org/W1965972569","https://openalex.org/W1979180832","https://openalex.org/W1980738513","https://openalex.org/W1992065791","https://openalex.org/W1995484833","https://openalex.org/W1997200791","https://openalex.org/W1999351024","https://openalex.org/W2006398000","https://openalex.org/W2006808488","https://openalex.org/W2007399394","https://openalex.org/W2010016018","https://openalex.org/W2010371250","https://openalex.org/W2015313928","https://openalex.org/W2016182223","https://openalex.org/W2025207305","https://openalex.org/W2030449718","https://openalex.org/W2040104067","https://openalex.org/W2043804332","https://openalex.org/W2045390367","https://openalex.org/W2045656233","https://openalex.org/W2058753770","https://openalex.org/W2059867647","https://openalex.org/W2067081844","https://openalex.org/W2075665712","https://openalex.org/W2080745194","https://openalex.org/W2097665501","https://openalex.org/W2101043704","https://openalex.org/W2116416291","https://openalex.org/W2116780995","https://openalex.org/W2117756735","https://openalex.org/W2121689290","https://openalex.org/W2122604533","https://openalex.org/W2124155943","https://openalex.org/W2124659530","https://openalex.org/W2128054898","https://openalex.org/W2128709328","https://openalex.org/W2129728285","https://openalex.org/W2133157266","https://openalex.org/W2135132414","https://openalex.org/W2144399314","https://openalex.org/W2144898279","https://openalex.org/W2145096794","https://openalex.org/W2152435742","https://openalex.org/W2157237396","https://openalex.org/W2160390548","https://openalex.org/W2167411378","https://openalex.org/W2171810522","https://openalex.org/W2229238337","https://openalex.org/W2245191586","https://openalex.org/W2296616510","https://openalex.org/W2400274291","https://openalex.org/W2496323672","https://openalex.org/W2582743722","https://openalex.org/W2610857016","https://openalex.org/W2615055317","https://openalex.org/W2787894218","https://openalex.org/W2798909945","https://openalex.org/W2911808754","https://openalex.org/W2949099125","https://openalex.org/W2949706644","https://openalex.org/W2949910245","https://openalex.org/W2952682616","https://openalex.org/W2953245254","https://openalex.org/W2962768290","https://openalex.org/W2963879412","https://openalex.org/W2963977107","https://openalex.org/W3098031065","https://openalex.org/W3099514962","https://openalex.org/W3101466063","https://openalex.org/W3120740533","https://openalex.org/W3122239533","https://openalex.org/W3139361274","https://openalex.org/W4205648292","https://openalex.org/W4233762729","https://openalex.org/W4250955649","https://openalex.org/W4253443994","https://openalex.org/W4312258136"],"related_works":["https://openalex.org/W2017034551","https://openalex.org/W2604963692","https://openalex.org/W228771216","https://openalex.org/W1768043922","https://openalex.org/W2964314781","https://openalex.org/W4389708677","https://openalex.org/W3006565005","https://openalex.org/W4287868071","https://openalex.org/W2611832276","https://openalex.org/W2001330101"],"abstract_inverted_index":{"This":[0,110],"article":[1],"deals":[2],"with":[3],"random":[4,30],"projections":[5,31],"applied":[6],"as":[7],"a":[8,56,71,98],"data":[9,37,64,69],"reduction":[10],"technique":[11],"for":[12,127],"Bayesian":[13,91,137],"regression":[14,93,152],"analysis.":[15],"We":[16],"show":[17],"sufficient":[18],"conditions":[19],"under":[20,29],"which":[21],"the":[22,34,45,62,67,78,87,118,144,151,161],"entire":[23],"d-dimensional":[24],"distribution":[25,89],"is":[26,94,147],"approximately":[27],"preserved":[28],"by":[32],"reducing":[33,160],"number":[35],"of":[36,66,77,90,106,121,136],"points":[38],"from":[39],"n":[40,47],"to":[41,97,149,155],"k":[42],"O(poly(d/))":[43],"in":[44,75],"case":[46,120],"d.":[48],"Under":[49],"mild":[50],"assumptions,":[51],"we":[52],"prove":[53],"that":[54,86,143],"evaluating":[55],"Gaussian":[57,115],"likelihood":[58],"function":[59],"based":[60],"on":[61,102],"projected":[63],"instead":[65],"original":[68],"yields":[70],"(1":[72],"+":[73],"O())-approximation":[74],"terms":[76],"2":[79],"Wasserstein":[80],"distance.":[81],"Our":[82,129,140],"main":[83],"result":[84],"shows":[85],"posterior":[88],"linear":[92,138],"approximated":[95],"up":[96,154],"small":[99,156],"error":[100,157],"depending":[101],"only":[103],"an":[104],"-fraction":[105],"its":[107],"defining":[108],"parameters.":[109],"holds":[111],"when":[112],"using":[113],"arbitrary":[114],"priors":[116],"or":[117],"degenerate":[119],"uniform":[122],"distributions":[123],"over":[124],"R":[125],"d":[126],".":[128],"empirical":[130],"evaluations":[131],"involve":[132],"different":[133],"simulated":[134],"settings":[135],"regression.":[139],"experiments":[141],"underline":[142],"proposed":[145],"method":[146],"able":[148],"recover":[150],"model":[153],"while":[158],"considerably":[159],"total":[162],"running":[163],"time.":[164]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":7},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":4},{"year":2015,"cited_by_count":1}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}