{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T14:33:35Z","timestamp":1775054015577,"version":"3.50.1"},"reference-count":13,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2003,6,1]],"date-time":"2003-06-01T00:00:00Z","timestamp":1054425600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2003,6,1]],"date-time":"2003-06-01T00:00:00Z","timestamp":1054425600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Machine Learning"],"published-print":{"date-parts":[[2003,6]]},"DOI":"10.1023\/a:1022905618164","type":"journal-article","created":{"date-parts":[[2003,4,7]],"date-time":"2003-04-07T18:16:51Z","timestamp":1049739411000},"page":"263-281","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Estimating the Optimal Margins of Embeddings in Euclidean Half Spaces"],"prefix":"10.1007","volume":"51","author":[{"given":"J\u00fcrgen","family":"Forster","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Niels","family":"Schmitt","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hans Ulrich","family":"Simon","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Thorsten","family":"Suttorp","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","reference":[{"key":"5120302_CR1","unstructured":"Ben-David, S. (2000). Personal Communication."},{"key":"5120302_CR2","first-page":"385","volume-title":"imitations of learning via embeddings in Euclidean half-spaces","author":"S. Ben-David","year":"2001","unstructured":"Ben-David, S., Eiron, N., & Simon, H. U. (2001). imitations of learning via embeddings in Euclidean half-spaces. To appear in the Journal of Machine Learning Research. A preliminary version appeared in the Proceedings of the 14th Annual Conference on Computational Learning Theory (pp. 385\u2013401). Berlin: Springer."},{"key":"5120302_CR3","first-page":"157","volume":"100","author":"A. Blumer","year":"1989","unstructured":"Blumer, A., Ehrenfeucht, A., Haussler, D., & Warmuth, M. K. (1989). Learnability and the Vapnik-Chervonenkis dimension. Journal of the ACM, 100, 157\u2013184.","journal-title":"Journal of the ACM"},{"key":"5120302_CR4","volume-title":"An Introduction to Support Vector Machines","author":"N. Cristianini","year":"2000","unstructured":"Cristianini, N., & Shawe-Taylor, J. (2000). An Introduction to Support Vector Machines. Cambridge, United Kingdom: Cambridge University Press."},{"key":"5120302_CR5","doi-asserted-by":"crossref","unstructured":"Forster, J. (2001). A linear lower bound on the unbounded error probabilistic communication complexity. In Proceedings of the 16th Annual IEEE Conference on Computational Complexity (pp. 100\u2013106). IEEE Computer Society Press.","DOI":"10.1109\/CCC.2001.933877"},{"key":"5120302_CR6","first-page":"171","volume-title":"Proceedings of the 21st Conference on Foundations of Software Technology and Theoretical Computer Science","author":"J. Forster","year":"2001","unstructured":"Forster, J., Krause, M., Lokam, S. V., Mubarakzjanov, R., Schmitt, N., & Simon, H. U. (2001). Relations between communication complexity, linear arrangements and computational complexity. In Proceedings of the 21st Conference on Foundations of Software Technology and Theoretical Computer Science (pp. 171\u2013182). Berlin: Springer."},{"key":"5120302_CR7","doi-asserted-by":"crossref","DOI":"10.1017\/CBO9780511810817","volume-title":"Matrix Analysis","author":"R. A. Horn","year":"1985","unstructured":"Horn, R. A.,& Johnson, C. R. (1985). Matrix Analysis. Cambridge, United Kingdom: Cambridge University Press."},{"key":"5120302_CR8","doi-asserted-by":"crossref","DOI":"10.7551\/mitpress\/3897.001.0001","volume-title":"An Introduction to Computational Learning Theory","author":"M. J. Kearns","year":"1994","unstructured":"Kearns, M. J., & Vazirani, U. V. (1994). An Introduction to Computational Learning Theory. Cambridge, Massachusetts: Massachusetts Institute of Technology."},{"key":"5120302_CR9","doi-asserted-by":"crossref","first-page":"99","DOI":"10.1016\/0304-3975(95)00005-4","volume":"156","author":"M. Krause","year":"1996","unstructured":"Krause, M. (1996). Geometric arguments yield better bounds for threshold circuits and distributed computing. Theoretical Computer Science, 156, 99\u2013117.","journal-title":"Theoretical Computer Science"},{"key":"5120302_CR10","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1023\/A:1022637031594","volume":"9","author":"W. Maass","year":"1992","unstructured":"Maass,W., & Turan, G. (1992). Lower bound methods and separation results for on-line learning models. Journal of Machine Learning, 9, 107\u2013145.","journal-title":"Journal of Machine Learning"},{"key":"5120302_CR11","first-page":"615","volume":"12","author":"A. B. Novikoff","year":"1962","unstructured":"Novikoff, A. B. (1962). On convergence proofs on perceptrons. Symposium on the Mathematical Theory of Automata, 12 (pp. 615\u2013622). Polytechnic Institute of Brooklyn.","journal-title":"Symposium on the Mathematical Theory of Automata"},{"key":"5120302_CR12","volume-title":"Statistical Learning Theory","author":"V. Vapnik","year":"1998","unstructured":"Vapnik, V. (1998). Statistical Learning Theory. New York: John Wiley & Sons, Inc."},{"key":"5120302_CR13","doi-asserted-by":"crossref","first-page":"264","DOI":"10.1137\/1116025","volume":"16","author":"V. N. Vapnik","year":"1971","unstructured":"Vapnik, V. N., & Chervonenkis, A. Y. (1971). On the uniform convergence of relative frequencies of events to their probabilities. Theory of Probability and its Applications, 16, 264\u2013280.","journal-title":"Theory of Probability and its Applications"}],"container-title":["Machine Learning"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1023\/A:1022905618164.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1023\/A:1022905618164\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1023\/A:1022905618164.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,10]],"date-time":"2025-07-10T11:36:23Z","timestamp":1752147383000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1023\/A:1022905618164"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2003,6]]},"references-count":13,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2003,6]]}},"alternative-id":["5120302"],"URL":"https:\/\/doi.org\/10.1023\/a:1022905618164","relation":{},"ISSN":["0885-6125","1573-0565"],"issn-type":[{"value":"0885-6125","type":"print"},{"value":"1573-0565","type":"electronic"}],"subject":[],"published":{"date-parts":[[2003,6]]},"assertion":[{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}