{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,27]],"date-time":"2025-11-27T06:25:14Z","timestamp":1764224714352},"reference-count":10,"publisher":"Wiley","issue":"4","license":[{"start":{"date-parts":[[2003,7,31]],"date-time":"2003-07-31T00:00:00Z","timestamp":1059609600000},"content-version":"vor","delay-in-days":152,"URL":"https:\/\/2.zoppoz.workers.dev:443\/http\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Complexity"],"published-print":{"date-parts":[[2003,3]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>We use the replica method of statistical physics to study the average case performance of learning systems. The new feature of our theory is that general distributions of data can be treated, which enables applications to real data. For a class of Bayesian prediction models which are based on Gaussian processes, we discuss Bootstrap estimates for learning curves. \u00a9 2003 Wiley Periodicals, Inc.<\/jats:p>","DOI":"10.1002\/cplx.10082","type":"journal-article","created":{"date-parts":[[2003,8,1]],"date-time":"2003-08-01T10:15:55Z","timestamp":1059732955000},"page":"57-63","source":"Crossref","is-referenced-by-count":4,"title":["Learning curves and bootstrap estimates for inference with Gaussian processes: A statistical mechanics study"],"prefix":"10.1002","volume":"8","author":[{"given":"D\u00f6rthe","family":"Malzahn","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Manfred","family":"Opper","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2003,7,31]]},"reference":[{"key":"e_1_2_1_2_2","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9781139164542"},{"key":"e_1_2_1_3_2","doi-asserted-by":"publisher","DOI":"10.1093\/acprof:oso\/9780198509417.001.0001"},{"key":"e_1_2_1_4_2","series-title":"Lecture Notes in Physics","volume-title":"Spin Glass Theory and Beyond","author":"M\u00e9zard M.","year":"1987"},{"key":"e_1_2_1_5_2","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611970128"},{"key":"e_1_2_1_6_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4612-0745-0"},{"key":"e_1_2_1_7_2","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevLett.77.4693"},{"key":"e_1_2_1_8_2","series-title":"Advances in Neural Information Processing Systems","first-page":"514","author":"Williams C.K.I.","year":"1996"},{"key":"e_1_2_1_9_2","volume-title":"Quantum Mechanics and Path Integrals","author":"Feynman R.P.","year":"1965"},{"key":"e_1_2_1_10_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4899-4541-9"},{"key":"e_1_2_1_11_2","unstructured":"The datasets can be downloaded from UCI Repository of Machine Learning Databases https:\/\/2.zoppoz.workers.dev:443\/http\/www1.ics.uci.edu\/\u223cmlearn\/MLSummary.html Irvine CA University of California Department of Information and Computer Science."}],"container-title":["Complexity"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/api.wiley.com\/onlinelibrary\/tdm\/v1\/articles\/10.1002%2Fcplx.10082","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/cplx.10082","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,12]],"date-time":"2023-09-12T05:08:37Z","timestamp":1694495317000},"score":1,"resource":{"primary":{"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/onlinelibrary.wiley.com\/doi\/10.1002\/cplx.10082"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2003,3]]},"references-count":10,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2003,3]]}},"alternative-id":["10.1002\/cplx.10082"],"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1002\/cplx.10082","archive":["Portico"],"relation":{},"ISSN":["1076-2787","1099-0526"],"issn-type":[{"value":"1076-2787","type":"print"},{"value":"1099-0526","type":"electronic"}],"subject":[],"published":{"date-parts":[[2003,3]]}}}