{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,5]],"date-time":"2024-09-05T18:15:57Z","timestamp":1725560157733},"publisher-location":"Berlin, Heidelberg","reference-count":52,"publisher":"Springer Berlin Heidelberg","isbn-type":[{"type":"print","value":"9783540407201"},{"type":"electronic","value":"9783540451679"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2003]]},"DOI":"10.1007\/978-3-540-45167-9_21","type":"book-chapter","created":{"date-parts":[[2010,7,22]],"date-time":"2010-07-22T19:10:53Z","timestamp":1279825853000},"page":"273-287","source":"Crossref","is-referenced-by-count":7,"title":["Boosting with Diverse Base Classifiers"],"prefix":"10.1007","author":[{"given":"Sanjoy","family":"Dasgupta","sequence":"first","affiliation":[]},{"given":"Philip M.","family":"Long","sequence":"additional","affiliation":[]}],"member":"297","reference":[{"key":"21_CR1","first-page":"173","volume":"24","author":"K.M. Ali","year":"1996","unstructured":"Ali, K.M., Pazzani, M.J.: Error reduction through learning multiple descriptions. Machine Learning\u00a024, 173\u2013202 (1996)","journal-title":"Machine Learning"},{"issue":"4","key":"21_CR2","doi-asserted-by":"crossref","first-page":"616","DOI":"10.1145\/263867.263927","volume":"44","author":"N. Alon","year":"1997","unstructured":"Alon, N., Ben-David, S., Cesa-Bianchi, N., Haussler, D.: Scale-sensitive dimensions, uniform convergence, and learnability. Journal of the Association for Computing Machinery\u00a044(4), 616\u2013631 (1997)","journal-title":"Journal of the Association for Computing Machinery"},{"key":"21_CR3","unstructured":"Amit, Y., Blanchard, G.: Multiple randomized classifiers: MRCL (2001) (manuscript)"},{"key":"21_CR4","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511624216","volume-title":"Neural Network Learning: Theoretical Foundations","author":"M. Anthony","year":"1999","unstructured":"Anthony, M., Bartlett, P.L.: Neural Network Learning: Theoretical Foundations. Cambridge University Press, Cambridge (1999)"},{"issue":"2","key":"21_CR5","doi-asserted-by":"publisher","first-page":"525","DOI":"10.1109\/18.661502","volume":"44","author":"P.L. Bartlett","year":"1998","unstructured":"Bartlett, P.L.: The sample complexity of pattern classification with neural networks: the size of the weights is more important than the size of the network. IEEE Transactions on Information Theory\u00a044(2), 525\u2013536 (1998)","journal-title":"IEEE Transactions on Information Theory"},{"key":"21_CR6","unstructured":"Bartlett, P.L., Jordan, M.I., McAuliffe, J.D.: Convexity, classification, and risk bounds. Technical Report 638, Department of Statistics, U.C. Berkeley (2003)"},{"key":"21_CR7","unstructured":"Blanchard, G., Lugosi, G., Vayatis, N.: On the rate of convergence of regularized boosting methods (2003) (manuscript)"},{"key":"21_CR8","doi-asserted-by":"crossref","unstructured":"Breiman, L.: Prediction games and arcing algorithms. Neural Computation\u00a011(7) (1999)","DOI":"10.1162\/089976699300016106"},{"key":"21_CR9","unstructured":"Breiman, L.: Some ininity theory for predictor ensembles. Technical Report 577, Statistics Department, UC Berkeley (2000)"},{"key":"21_CR10","unstructured":"Breiman, L.: Arcing classiiers. The Annals of Statistics (1998)"},{"key":"21_CR11","unstructured":"B\u00fclmann, P., Yu, B.: Boosting with the l2 loss: regression and classification. Journal of the American Statistical Association (to appear)"},{"issue":"2","key":"21_CR12","doi-asserted-by":"publisher","first-page":"99","DOI":"10.1002\/(SICI)1098-2418(199809)13:2<99::AID-RSA1>3.0.CO;2-M","volume":"13","author":"D. Dubhashi","year":"1998","unstructured":"Dubhashi, D., Ranjan, D.: Balls and bins: A study in negative dependence. Random Structures & Algorithms\u00a013(2), 99\u2013124 (1998)","journal-title":"Random Structures & Algorithms"},{"issue":"457","key":"21_CR13","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1198\/016214502753479248","volume":"97","author":"S. Dudoit","year":"2002","unstructured":"Dudoit, S., Fridlyand, J., Speed, T.P.: Comparison of discrimination methods for the classiication of tumors using gene expression data. Journal of the American Statistical Association\u00a097(457), 77\u201387 (2002)","journal-title":"Journal of the American Statistical Association"},{"issue":"2","key":"21_CR14","doi-asserted-by":"publisher","first-page":"256","DOI":"10.1006\/inco.1995.1136","volume":"121","author":"Y. Freund","year":"1995","unstructured":"Freund, Y.: Boosting a weak learning algorithm by majority. Information and Computation\u00a0121(2), 256\u2013285 (1995)","journal-title":"Information and Computation"},{"key":"21_CR15","unstructured":"Freund, Y., Schapire, R.: Experiments with a new boosting algorithm. In: Proceedings of the 13th International Conference on Machine Learning (1996)"},{"key":"21_CR16","doi-asserted-by":"crossref","unstructured":"Freund, Y., Schapire, R.E.: A decision-theoretic generalization of on-line learning and an application to boosting. In: Proceedings of the 2nd European Conference on Computational Learning Theory, pp. 23-37 (1995)","DOI":"10.1007\/3-540-59119-2_166"},{"issue":"2","key":"21_CR17","doi-asserted-by":"publisher","first-page":"337","DOI":"10.1214\/aos\/1016218223","volume":"38","author":"J. Friedman","year":"2000","unstructured":"Friedman, J., Hastie, T., Tibshirani, R.: Additive logistic regression: A statistical view of boosting. The Annals of Statistics\u00a038(2), 337\u2013407 (2000)","journal-title":"The Annals of Statistics"},{"key":"21_CR18","doi-asserted-by":"crossref","unstructured":"Gavinsky, D.: Optimally-smooth adaptive boosting and application to agnostic learning. In: Proceedings of the 13th International Workshop on Algorithmic Learning Theory (2002)","DOI":"10.1007\/3-540-36169-3_10"},{"key":"21_CR19","unstructured":"Grove, A.J., Schuurmans, D.: Boosting in the limit: Maximizing the margin of learned ensembles. In: Proceedings of the 15th National Conference on Artifical Intelligence (1998)"},{"key":"21_CR20","doi-asserted-by":"crossref","first-page":"129","DOI":"10.1016\/0022-0000(93)90001-D","volume":"46","author":"A. Hajnal","year":"1993","unstructured":"Hajnal, A., Maass, W., Pudl\u00e1k, P., Szegedy, M., Tur\u00e1n, G.: Threshold circuits of bounded depth. Journal of Computer and System Sciences\u00a046, 129\u2013154 (1993)","journal-title":"Journal of Computer and System Sciences"},{"key":"21_CR21","doi-asserted-by":"crossref","unstructured":"Impagliazzo, R.: Hard-core distributions for somewhat hard problems. In: IEEE Symposium on Foundations of Computer Science, pp. 538-545 (1995)","DOI":"10.1109\/SFCS.1995.492584"},{"key":"21_CR22","doi-asserted-by":"crossref","unstructured":"Jiang, W.: Process consistency for AdaBoost. Annals of Statistics (to appear)","DOI":"10.1214\/aos\/1079120128"},{"key":"21_CR23","doi-asserted-by":"crossref","unstructured":"Klivans, A., Servedio, R.A.: Boosting and hard-core sets. In: IEEE Symposium on Foundations of Computer Science, pp. 624-633 (1999)","DOI":"10.1109\/SFFCS.1999.814638"},{"key":"21_CR24","doi-asserted-by":"crossref","unstructured":"Koltchinskii, V., Panchenko, D.: Empirical margin distributions and bounding the generalization error of combined classiiers. Annals of Statistics\u00a030(1) (2002)","DOI":"10.1214\/aos\/1015362183"},{"key":"21_CR25","unstructured":"Koltchinskii, V., Panchenko, D.: Complexities of convex combinations and bounding the generalization error in classiication (2003) (manuscript)"},{"key":"21_CR26","unstructured":"Langford, J., Shawe-Taylor, J.: PAC-bayes and margins. In: NIPS (2002)"},{"key":"21_CR27","volume-title":"Monte Carlo Strategies in Scientific Computing","author":"J.S. Liu","year":"2001","unstructured":"Liu, J.S.: Monte Carlo Strategies in Scientific Computing. Springer, Heidelberg (2001)"},{"issue":"443","key":"21_CR28","doi-asserted-by":"crossref","first-page":"1032","DOI":"10.1080\/01621459.1998.10473765","volume":"93","author":"J.S. Liu","year":"1998","unstructured":"Liu, J.S., Chen, R.: Sequential Monte Carlo methods for dynamic systems. Journal of the American Statistical Association\u00a093(443), 1032\u20131044 (1998)","journal-title":"Journal of the American Statistical Association"},{"key":"21_CR29","unstructured":"Long, P.M.: Minimum majority classiication and boosting. In: Proceedings of the The 18th National Conference on Artificial Intelligence (2002)"},{"key":"21_CR30","unstructured":"Long, P.M., Vega, V.B.: Boosting and microarray data. Machine Learning (to appear)"},{"key":"#cr-split#-21_CR31.1","doi-asserted-by":"crossref","unstructured":"Lugosi, G., Vayatis, N.: On the bayes-risk consistency of regularized boosting methods. Annals of Statistics (2004);","DOI":"10.1214\/aos\/1079120129"},{"key":"#cr-split#-21_CR31.2","unstructured":"Preliminary version in COLT 2002 (2002)"},{"key":"21_CR32","unstructured":"Mannor, S., Meir, R., Mendelson, S.: The consistency of boosting algorithms (2001) (manuscript)"},{"key":"21_CR33","doi-asserted-by":"crossref","unstructured":"Mannor, S., Meir, R., Zhang, T.: The consistency of greedy algorithms for classification. In: Proc. 15th Annual Conference on Computational Learning Theory (2002)","DOI":"10.1007\/3-540-45435-7_22"},{"key":"21_CR34","first-page":"211","volume-title":"Proc. 14th International Conference on Machine Learning","author":"D.D. Margineantu","year":"1997","unstructured":"Margineantu, D.D., Dietterich, T.G.: Pruning adaptive boosting. In: Proc. 14th International Conference on Machine Learning, pp. 211\u2013218. Morgan Kaufmann, San Francisco (1997)"},{"key":"21_CR35","first-page":"512","volume-title":"Advances in Neural Information Processing Systems","author":"L. Mason","year":"2000","unstructured":"Mason, L., Baxter, J., Bartlett, P.L., Frean, M.: Boosting algorithms as gradient descent. In: Advances in Neural Information Processing Systems, vol.\u00a012, pp. 512\u2013518. MIT Press, Cambridge (2000)"},{"issue":"3","key":"21_CR36","doi-asserted-by":"publisher","first-page":"243","DOI":"10.1023\/A:1007697429651","volume":"38","author":"L. Mason","year":"2000","unstructured":"Mason, L., Bartlett, P.L., Baxter, J.: Improved generalization through explicit optimization of margins. Machine Learning\u00a038(3), 243\u2013255 (2000)","journal-title":"Machine Learning"},{"key":"21_CR37","doi-asserted-by":"crossref","unstructured":"McAllester, D.: Simplified PAC-Bayesian margin bounds. In: Proceedings of the 2003 Conference on Computational Learning Theory (2003)","DOI":"10.1007\/978-3-540-45167-9_16"},{"key":"21_CR38","first-page":"164","volume-title":"Proc. 12th Annu. Conf. on Comput. Learning Theory","author":"D.A. McAllester","year":"1999","unstructured":"McAllester, D.A.: PAC-Bayesian model averaging. In: Proc. 12th Annu. Conf. on Comput. Learning Theory, pp. 164\u2013170. ACM Press, New York (1999)"},{"issue":"3","key":"21_CR39","doi-asserted-by":"publisher","first-page":"355","DOI":"10.1023\/A:1007618624809","volume":"37","author":"D.A. McAllester","year":"1999","unstructured":"McAllester, D.A.: Some PAC-Bayesian theorems. Machine Learning\u00a037(3), 355\u2013363 (1999)","journal-title":"Machine Learning"},{"key":"21_CR40","doi-asserted-by":"crossref","DOI":"10.1017\/CBO9780511814075","volume-title":"Randomized Algorithms","author":"R. Motwani","year":"1995","unstructured":"Motwani, R., Raghavan, P.: Randomized Algorithms. Cambridge University Press, Cambridge (1995)"},{"key":"21_CR41","unstructured":"Niyogi, P., Pierrot, J.-B., Siohan, O.: On decorrelating classifiers and combining them (2001) (manuscript), see http:\/\/people.cs.uchicago.edu\/~niyogi\/decorrelation.ps"},{"issue":"12","key":"21_CR42","first-page":"1980","volume":"1","author":"G. Pisier","year":"1981","unstructured":"Pisier, G.: Remarques sur un resultat non publi\u2019e de B. Maurey. Sem. d\u2019Analyse Fonctionelle\u00a01(12), 1980\u20131981 (1981)","journal-title":"Maurey. Sem. d\u2019Analyse Fonctionelle"},{"key":"21_CR43","unstructured":"Quinlan, J.: Bagging, boosting and c4.5. In: Proceedings of the 13th National Conference on Artifiicial Intelligence, pp. 725\u2013730. AAAI\/MIT Press (1996)"},{"key":"21_CR44","doi-asserted-by":"crossref","unstructured":"R\u00e4tsch, G., Warmuth, M.K.: Marginal boosting. In: Proceedings of the Annual Conference on Computational Learning Theory (2002)","DOI":"10.1007\/3-540-45435-7_23"},{"key":"21_CR45","unstructured":"Rosset, S., Zhu, J., Hastie, T.: Boosting as a regularized path to a maximum margin classiier. In: NIPS (2002)"},{"key":"21_CR46","first-page":"197","volume":"5","author":"R. Schapire","year":"1990","unstructured":"Schapire, R.: The strength of weak learnability. Machine Learning\u00a05, 197\u2013227 (1990)","journal-title":"Machine Learning"},{"issue":"5","key":"21_CR47","doi-asserted-by":"publisher","first-page":"1651","DOI":"10.1214\/aos\/1024691352","volume":"26","author":"R.E. Schapire","year":"1998","unstructured":"Schapire, R.E., Freund, Y., Bartlett, P., Lee, W.S.: Boosting the margin: A new explanation for the effectiveness of voting methods. The Annals of Statistics\u00a026(5), 1651\u20131686 (1998)","journal-title":"The Annals of Statistics"},{"key":"21_CR48","unstructured":"Southey, F., Schuurmans, D., Ghodsi, A.: Regularized greedy importance sampling. In: NIPS 2002 (2002)"},{"issue":"20","key":"21_CR49","doi-asserted-by":"publisher","first-page":"11462","DOI":"10.1073\/pnas.201162998","volume":"98","author":"M. West","year":"2001","unstructured":"West, M., et al.: Predicting the clinical status of human breast cancer by using gene expression profiles. Proc. Natl. Acad. Sci. USA\u00a098(20), 11462\u201311467 (2001)","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"21_CR50","unstructured":"Zhang, T.: Statistical behavior and consistency of classiication methods based on convex risk minimization. Annals of Statistics (to appear)"},{"key":"21_CR51","unstructured":"Zhang, T., Yu, B.: Boosting with early stopping: convergence and consistency. Technical Report 635, Statistics Department, UC Berkeley (2003)"}],"container-title":["Lecture Notes in Computer Science","Learning Theory and Kernel Machines"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-540-45167-9_21","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,5,31]],"date-time":"2019-05-31T08:59:33Z","timestamp":1559293173000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-540-45167-9_21"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2003]]},"ISBN":["9783540407201","9783540451679"],"references-count":52,"URL":"https:\/\/doi.org\/10.1007\/978-3-540-45167-9_21","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2003]]}}}