{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,29]],"date-time":"2026-05-29T13:18:38Z","timestamp":1780060718480,"version":"3.54.0"},"reference-count":26,"publisher":"Springer Science and Business Media LLC","issue":"1-3","license":[{"start":{"date-parts":[[2002,1,1]],"date-time":"2002-01-01T00:00:00Z","timestamp":1009843200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2002,1,1]],"date-time":"2002-01-01T00:00:00Z","timestamp":1009843200000},"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":[[2002,1]]},"DOI":"10.1023\/a:1012470815092","type":"journal-article","created":{"date-parts":[[2002,12,23]],"date-time":"2002-12-23T08:38:06Z","timestamp":1040632686000},"page":"225-254","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":273,"title":["Linear Programming Boosting via Column Generation"],"prefix":"10.1007","volume":"46","author":[{"given":"Ayhan","family":"Demiriz","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kristin P.","family":"Bennett","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"John","family":"Shawe-Taylor","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","reference":[{"key":"380506_CR1","doi-asserted-by":"crossref","DOI":"10.1017\/CBO9780511624216","volume-title":"Learning in neural networks: Theoretical foundations","author":"M. Anthony","year":"1999","unstructured":"Anthony, M. & Bartlett, P. (1999). Learning in neural networks: Theoretical foundations. Cambridge: Cambridge University Press."},{"key":"380506_CR2","doi-asserted-by":"crossref","first-page":"105","DOI":"10.1023\/A:1007515423169","volume":"36","author":"E. Bauer","year":"1999","unstructured":"Bauer, E. & Kohavi, R. (1999). An empirical comparison of voting classification algorithms: Bagging, boosting, and variants. Machine Learning, 36, 105-139.","journal-title":"Machine Learning"},{"key":"380506_CR3","first-page":"307","volume-title":"Advances in kernel methods-Support vector machines","author":"K. P. Bennett","year":"1999","unstructured":"Bennett, K. P. (1999). Combining support vector and mathematical programming methods for classification. In B. Sch\u00f6lkopf, C. Burges, & A. Smola (Eds.). Advances in kernel methods-Support vector machines (pp. 307-326). Cambridge, MA: MIT Press."},{"key":"380506_CR4","first-page":"57","volume-title":"Proceedings of the 17th International Conference on Machine Learning","author":"K. Bennett","year":"2000","unstructured":"Bennett, K. & Bredensteiner, E. J. (2000). Duality and geometry in svm classifiers. In P. Langley (Ed.). Proceedings of the 17th International Conference on Machine Learning (pp. 57-64). San Mateo, CA: Morgan Kaufmann."},{"key":"380506_CR5","first-page":"368","volume-title":"Advances in neural information processing systems 11","author":"K. P. Bennett","year":"1999","unstructured":"Bennett, K. P. & Demiriz, A. (1999). Semi-supervised support vector machines. In M. Kearns & S. Solla, D. C. (Ed.). Advances in neural information processing systems 11 (pp. 368-374). Cambridge, MA: MIT Press."},{"key":"380506_CR6","first-page":"65","volume-title":"Proceedings of Seventeenth International Conference on Machine Learning (ICML' 2000)","author":"K. P. Bennett","year":"2000","unstructured":"Bennett, K. P., Demiriz, A., & Shawe-Taylor, J. (2000). A column generation approach to boosting. In P. Langley (Ed.), Proceedings of Seventeenth International Conference on Machine Learning (ICML' 2000) (pp. 65-72). San Francisco, CA: Morgan Kaufmann."},{"key":"380506_CR7","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1080\/10556789208805504","volume":"1","author":"K. P. Bennett","year":"1992","unstructured":"Bennett, K. P. & Mangasarian, O. L. (1992). Robust linear programming discrimination of two linearly inseparable sets. Optimization Methods and Software, 1, 23-34.","journal-title":"Optimization Methods and Software"},{"key":"380506_CR8","first-page":"144","volume-title":"Proceedings of the 5th Annual ACM Workshop on Computational Learning Theory","author":"B. E. Boser","year":"1992","unstructured":"Boser, B. E., Guyon, I. M., & Vapnik, V. N. (1992). A training algorithm for optimal margin classifiers. In D. Haussler (Ed.). Proceedings of the 5th Annual ACM Workshop on Computational Learning Theory (pp. 144-152). New York: ACM Press."},{"issue":"7","key":"380506_CR9","doi-asserted-by":"crossref","first-page":"1493","DOI":"10.1162\/089976699300016106","volume":"11","author":"L. Breiman","year":"1999","unstructured":"Breiman, L. (1999). Prediction games and arcing algorithms. Neural Computation, 11:7, 1493-1517.","journal-title":"Neural Computation"},{"key":"380506_CR10","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1023\/A:1022627411411","volume":"20","author":"C. Cortes","year":"1995","unstructured":"Cortes, C. & Vapnik, V. (1995). Support vector networks. Machine Learning, 20, 273-297.","journal-title":"Machine Learning"},{"key":"380506_CR11","unstructured":"CPLEX Optimization Incorporated, Incline Village, Nevada (1994). Using the CPLEX Callabe Library."},{"key":"380506_CR12","volume-title":"An introduction to support vector machines","author":"N. Cristianni","year":"2000","unstructured":"Cristianni, N. & Shawe-Taylor, J. (2000). An introduction to support vector machines. Cambridge: Cambridge University Press."},{"key":"380506_CR13","unstructured":"Grove, A. & Schuurmans, D. (1998). Boosting in the limit: Maximizing the margin of learned ensembles. In Proceedings of the Fifteenth National Conference on Artificial Intelligence, AAAI-98."},{"key":"380506_CR14","doi-asserted-by":"crossref","first-page":"444","DOI":"10.1287\/opre.13.3.444","volume":"13","author":"O. L. Mangasarian","year":"1995","unstructured":"Mangasarian, O. L. (1995). Linear and nonlinear separation of patterns by linear programming. Operations Research, 13, 444-452.","journal-title":"Operations Research"},{"key":"380506_CR15","doi-asserted-by":"crossref","first-page":"135","DOI":"10.7551\/mitpress\/1113.003.0012","volume-title":"Advances in large margin classifiers","author":"O. L. Mangasarian","year":"2000","unstructured":"Mangasarian, O. L. (2000). Generalized support vector machines. In A. Smola, P. Bartlett, B. Sch\u00f6lkopf, & D. Schuurmans (Eds.), Advances in large margin classifiers (pp. 135-146). Cambridge, MA: MIT Press. ftp:\/\/ftp.cs.wisc.edu\/math-prog\/tech-reports\/98-14.ps."},{"key":"380506_CR16","volume-title":"UCI repository of machine learning databases","author":"P. Murphy","year":"1992","unstructured":"Murphy, P. & Aha, D. (1992). UCI repository of machine learning databases. Department of Information and Computer Science, Irvine, California: University of California."},{"key":"380506_CR17","volume-title":"Linear and nonlinear programming","author":"S. Nash","year":"1996","unstructured":"Nash, S. & Sofer, A. (1996). Linear and nonlinear programming. New York, NY: McGraw-Hill."},{"key":"380506_CR18","volume-title":"Proceedings of the 13th National Conference on Artificial Intelligence","author":"J. Quinlan","year":"1996","unstructured":"Quinlan, J. (1996). Bagging, boosting, and C4.5. In Proceedings of the 13th National Conference on Artificial Intelligence, Menlo Park, CA: AAAI Press."},{"key":"380506_CR19","doi-asserted-by":"crossref","first-page":"207","DOI":"10.7551\/mitpress\/1113.003.0016","volume-title":"Advances in large margin classifiers","author":"G. R\u00e4tsch","year":"2000","unstructured":"R\u00e4tsch, G., Sch\u00f6lkopf, B., Smola, A., Mika, S., Onoda, T., & M\u00fcller, K.-R. (2000a). Robust ensemble learning. In A. Smola, P. Bartlett, B. Sch\u00f6lkopf, & D. Schuurmans (Eds.). Advances in large margin classifiers (pp. 207-219). Cambridge, MA: MIT Press."},{"key":"380506_CR20","volume-title":"Advances in neural information processing systems 12","author":"G. R\u00e4tsch","year":"2000","unstructured":"R\u00e4tsch, G., Sch\u00f6lkopf, B., Smola, A., M\u00fcller, K.-R., Onoda, T., & Mika, S. (2000b). v-arc ensemble learning in the presence of outliers. In S. A. Solla, T. Leen, & K.-R. M\u00fcller (Eds.). Advances in neural information processing systems 12. Cambridge, MA: MIT Press."},{"key":"380506_CR21","unstructured":"R\u00e4tsch, G., Warmuth, M., Mika, S., Onoda, T., Lemm, S., & M\u00fcller, K.-R. (2000c). Barrier boosting. Technical Report."},{"issue":"5","key":"380506_CR22","first-page":"1651","volume":"26","author":"R. Schapire","year":"1998","unstructured":"Schapire, R., Freund, Y., Bartlett, P., & Lee, W. S. (1998). Boosting the margin: A new explanation for the effectiveness of voting methods. Annals of Statistics, 26:5, 1651-1686.","journal-title":"Annals of Statistics"},{"issue":"3","key":"380506_CR23","doi-asserted-by":"crossref","first-page":"297","DOI":"10.1023\/A:1007614523901","volume":"37","author":"R. Schapire","year":"1998","unstructured":"Schapire, R. & Singer, Y. (1998). Improved boosting algorithms using confidence-rated predictions. Machine Learning, 37:3, 297-336.","journal-title":"Machine Learning"},{"issue":"5","key":"380506_CR24","doi-asserted-by":"crossref","first-page":"1926","DOI":"10.1109\/18.705570","volume":"44","author":"J. Shawe-Taylor","year":"1998","unstructured":"Shawe-Taylor, J., Bartlett, P. L., Williamson, R. C., & Anthony, M. (1998). Structural risk minimization over data-dependent hierarchies. IEEE Transactions on Information Theory, 44:5, 1926-1940.","journal-title":"IEEE Transactions on Information Theory"},{"key":"380506_CR25","doi-asserted-by":"crossref","unstructured":"Shawe-Taylor, J. & Cristianini, N. (1999). Margin distribution bounds on generalization. In Proceedings of the European Conference on Computational Learning Theory, EuroCOLT'99 (pp. 263-273).","DOI":"10.1007\/3-540-49097-3_21"},{"key":"380506_CR26","unstructured":"Zhang, T. (1999). Analysis of regularized linear functions for classification problems. Technical Report RC-21572, IBM."}],"container-title":["Machine Learning"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1023\/A:1012470815092.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1023\/A:1012470815092\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1023\/A:1012470815092.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,10]],"date-time":"2025-07-10T11:32:03Z","timestamp":1752147123000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1023\/A:1012470815092"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2002,1]]},"references-count":26,"journal-issue":{"issue":"1-3","published-print":{"date-parts":[[2002,1]]}},"alternative-id":["380506"],"URL":"https:\/\/doi.org\/10.1023\/a:1012470815092","relation":{},"ISSN":["0885-6125","1573-0565"],"issn-type":[{"value":"0885-6125","type":"print"},{"value":"1573-0565","type":"electronic"}],"subject":[],"published":{"date-parts":[[2002,1]]},"assertion":[{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}