{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T07:41:56Z","timestamp":1781077316716,"version":"3.54.1"},"reference-count":9,"publisher":"Springer Science and Business Media LLC","issue":"2-3","license":[{"start":{"date-parts":[[2006,5,8]],"date-time":"2006-05-08T00:00:00Z","timestamp":1147046400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Mach Learn"],"published-print":{"date-parts":[[2007,3]]},"DOI":"10.1007\/s10994-006-8638-3","type":"journal-article","created":{"date-parts":[[2006,5,8]],"date-time":"2006-05-08T12:32:50Z","timestamp":1147091570000},"page":"151-163","source":"Crossref","is-referenced-by-count":8,"title":["A new PAC bound for intersection-closed concept classes"],"prefix":"10.1007","volume":"66","author":[{"given":"Peter","family":"Auer","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ronald","family":"Ortner","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2006,5,8]]},"reference":[{"issue":"1","key":"8638_CR1","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1016\/S0304-3975(97)00019-4","volume":"185","author":"P. Auer","year":"1997","unstructured":"Auer, P. (1997). Learning nested differences in the presence of malicious noise. Theor. Comput. Sci., 185(1), 159\u2013175.","journal-title":"Theor. Comput. Sci."},{"key":"8638_CR2","doi-asserted-by":"crossref","unstructured":"Auer, P., & Cesa-Bianchi, N. (1998). On-line learning with malicious noise and the closure algorithm. Ann. Math. Artif. Intell., 23 (1\u20132), 83\u201399.","DOI":"10.1023\/A:1018960107028"},{"key":"8638_CR3","doi-asserted-by":"crossref","unstructured":"Auer, P., Long, P.M., & Srinivasan, A. (1998). Approximating hyper-rectangles: Learning and pseudorandom sets. J. Comput. Syst. Sci., 57(3), 376\u2013388.","DOI":"10.1006\/jcss.1998.1593"},{"issue":"4","key":"8638_CR4","doi-asserted-by":"crossref","first-page":"929","DOI":"10.1145\/76359.76371","volume":"36","author":"A. Blumer","year":"1989","unstructured":"Blumer, A., Ehrenfeucht, A., Haussler, D., & Warmuth, M. (1989). Learnability and the Vapnik-Chervonenkis dimension. J. ACM, 36(4), 929\u2013965.","journal-title":"J. ACM"},{"issue":"3","key":"8638_CR5","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1016\/0890-5401(89)90002-3","volume":"82","author":"A. Ehrenfeucht","year":"1989","unstructured":"Ehrenfeucht, A., Haussler, D., Kearns, M. J., & Valiant, L. G. (1989). A general lower bound on the number of examples needed for learning. Inf. Comput., 82(3), 247\u2013261.","journal-title":"Inf. Comput."},{"issue":"3","key":"8638_CR6","first-page":"269","volume":"21","author":"A. Floyd","year":"1995","unstructured":"Floyd, A., & Warmuth, M. (1995). Sample compression, learnability, and the Vapnik-Chervonenkis Dimension. Machine Learning, 21(3), 269\u2013304.","journal-title":"Machine Learning"},{"issue":"2","key":"8638_CR7","doi-asserted-by":"crossref","first-page":"248","DOI":"10.1006\/inco.1994.1097","volume":"115","author":"D. Haussler","year":"1994","unstructured":"Haussler, D., Littlestone, N., & Warmuth, M. (1994). Predicting {l0,1}-functions on randomly drawn points. Inf. Comput., 115(2), 248\u2013292.","journal-title":"Inf. Comput."},{"key":"8638_CR8","first-page":"165","volume":"5","author":"D. Helmbold","year":"1990","unstructured":"Helmbold, D., Sloan, R., & Warmuth, M. (1990). Learning nested differences of intersection-closed concept classes. Machine Learning 5, 165\u2013196.","journal-title":"Machine Learning"},{"key":"8638_CR9","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1016\/0097-3165(72)90019-2","volume":"13","author":"N. Sauer","year":"1972","unstructured":"Sauer, N. (1972). On the density of families of sets. J. Combin. Theory Ser. A, 13, 145\u2013147.","journal-title":"J. Combin. Theory Ser. A"}],"container-title":["Machine Learning"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10994-006-8638-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10994-006-8638-3\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10994-006-8638-3","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,5,31]],"date-time":"2019-05-31T21:40:21Z","timestamp":1559338821000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10994-006-8638-3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2006,5,8]]},"references-count":9,"journal-issue":{"issue":"2-3","published-print":{"date-parts":[[2007,3]]}},"alternative-id":["8638"],"URL":"https:\/\/doi.org\/10.1007\/s10994-006-8638-3","relation":{},"ISSN":["0885-6125","1573-0565"],"issn-type":[{"value":"0885-6125","type":"print"},{"value":"1573-0565","type":"electronic"}],"subject":[],"published":{"date-parts":[[2006,5,8]]}}}