Robert E. Schapire - Publications

Affiliations: 
Princeton University, Princeton, NJ 
Area:
Mathematics, Computer Science, Statistics

90 high-probability publications. We are testing a new system for linking publications to authors. You can help! If you notice any inaccuracies, please sign in and mark papers as correct or incorrect matches. If you identify any major omissions or other inaccuracies in the publication list, please let us know.

Year Citation  Score
2016 Freund Y, Schapire RE. A decision-theoretic generalization of on-line learning and an application to boosting Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 904: 23-37.  1
2016 Freund Y, Schapire RE. A decision-theoretic generalization of on-line learning and an application to boosting Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 904: 23-37.  1
2015 Wang Z, Schapire RE, Verma N. Error Adaptive Classifier Boosting (EACB): Leveraging Data-Driven Training Towards Hardware Resilience for Signal Inference Ieee Transactions On Circuits and Systems I: Regular Papers. 62: 1136-1145. DOI: 10.1109/TCSI.2015.2395591  1
2015 Syrgkanis V, Agarwal A, Luo H, Schapire RE. Fast convergence of regularized learning in games Advances in Neural Information Processing Systems. 2015: 2989-2997.  1
2015 Kapicioglu B, Rosenberg DS, Schapire RE, Jebara T. Collaborative place models Ijcai International Joint Conference On Artificial Intelligence. 2015: 3612-3618.  1
2015 Huang TK, Agarwal A, Hsu D, Langford J, Schapire RE. Efficient and parsimonious agnostic active learning Advances in Neural Information Processing Systems. 2015: 2755-2763.  1
2014 Lozano AC, Kulkarni SR, Schapire RE. Convergence and consistency of regularized boosting with weakly dependent observations Ieee Transactions On Information Theory. 60: 651-660. DOI: 10.1109/TIT.2013.2287726  1
2014 Luo H, Schapire RE. A drifting-games analysis for online learning and applications to boosting Advances in Neural Information Processing Systems. 2: 1368-1376.  1
2014 Luo H, Schapire RE. Towards minimax online learning with unknown time horizon 31st International Conference On Machine Learning, Icml 2014. 1: 378-397.  1
2014 Kapicioglu B, Rosenberg DS, Schapire RE, Jebara T. Collaborative ranking for local preferences Journal of Machine Learning Research. 33: 466-474.  1
2014 Agarwal A, Badanidiyuru A, Dudík M, Schapire RE, Slivkins A. Robust multi-objective learning with mentor feedback Journal of Machine Learning Research. 35: 726-741.  1
2014 Agarwal A, Hsu D, Kale S, Langford J, Li L, Schapire RE. Taming the monster: A fast and simple algorithm for contextual bandits 31st International Conference On Machine Learning, Icml 2014. 5: 3611-3619.  1
2013 Schapire RE. Explaining adaboost Empirical Inference: Festschrift in Honor of Vladimir N. Vapnik. 37-52. DOI: 10.1007/978-3-642-41136-6_5  1
2013 Mukherjee I, Rudin C, Schapire RE. The rate of convergence of AdaBoost Journal of Machine Learning Research. 14: 2315-2347.  1
2013 Mukherjee I, Rudin C, Schapire RE. The rate of convergence of AdaBoost Journal of Machine Learning Research. 14: 2315-2347.  1
2012 Agarwal A, Dudík M, Kale S, Langford J, Schapire RE. Contextual bandit learning with predictable rewards Journal of Machine Learning Research. 22: 19-26.  1
2011 Jafarpour S, Cevher V, Schapire RE. A game theoretic approach to expander-based compressive sensing Ieee International Symposium On Information Theory - Proceedings. 464-468. DOI: 10.1109/ISIT.2011.6034169  1
2011 Jafarpour S, Schapire RE, Cevher V. Compressive sensing meets game theory Icassp, Ieee International Conference On Acoustics, Speech and Signal Processing - Proceedings. 3660-3663. DOI: 10.1109/ICASSP.2011.5947144  1
2011 Chu W, Li L, Reyzin L, Schapire RE. Contextual bandits with linear Payoff functions Journal of Machine Learning Research. 15: 208-214.  1
2011 Beygelzimer A, Langford J, Li L, Reyzin L, Schapire RE. Contextual bandit algorithms with supervised learning guarantees Journal of Machine Learning Research. 15: 19-26.  1
2010 Li L, Chu W, Langford J, Schapire RE. A contextual-bandit approach to personalized news article recommendation Proceedings of the 19th International Conference On World Wide Web, Www '10. 661-670. DOI: 10.1145/1772690.1772758  1
2010 Mukherjee I, Schapire RE. Learning with continuous experts using drifting games Theoretical Computer Science. 411: 2670-2683. DOI: 10.1016/j.tcs.2010.04.004  1
2010 Schapire RE. The convergence rate of AdaBoost Colt 2010 - the 23rd Conference On Learning Theory. 308-309.  1
2010 Mukherjee I, Schapire RE. A theory of multiclass boosting Advances in Neural Information Processing Systems 23: 24th Annual Conference On Neural Information Processing Systems 2010, Nips 2010 1
2010 Syed U, Schapire RE. A reduction from apprenticeship learning to classification Advances in Neural Information Processing Systems 23: 24th Annual Conference On Neural Information Processing Systems 2010, Nips 2010 1
2010 Kapicioglu B, Schapire RE, Wikelski M, Broderick T. Combining spatial and telemetric features for learning animal movement models Proceedings of the 26th Conference On Uncertainty in Artificial Intelligence, Uai 2010. 260-267.  1
2009 Barutcuoglu Z, Airoldi EM, Dumeaux V, Schapire RE, Troyanskaya OG. Aneuploidy prediction and tumor classification with heterogeneous hidden conditional random fields. Bioinformatics (Oxford, England). 25: 1307-13. PMID 19052061 DOI: 10.1093/bioinformatics/btn585  1
2009 Bradley JK, Schapire RE. FilterBoost: Regression and classification on large datasets Advances in Neural Information Processing Systems 20 - Proceedings of the 2007 Conference 1
2009 Syed U, Schapire RE. A game-theoretic approach to apprenticeship learning Advances in Neural Information Processing Systems 20 - Proceedings of the 2007 Conference 1
2009 Rudin C, Schapire RE. Margin-based ranking and an equivalence between AdaBoost and RankBoost Journal of Machine Learning Research. 10: 2193-2232.  1
2009 Xi YT, Xiang ZJ, Ramadge PJ, Schapire RE. Speed and sparsity of regularized boosting Journal of Machine Learning Research. 5: 615-622.  1
2008 Wisz MS, Hijmans RJ, Li J, Peterson AT, Graham CH, Guisan A, Elith J, Dudík M, Ferrier S, Huettmann F, Leathwick JR, Lehmann A, Lohmann L, Loiselle BA, Manion G, ... ... Schapire RE, et al. Effects of sample size on the performance of species distribution models Diversity and Distributions. 14: 763-773. DOI: 10.1111/j.1472-4642.2008.00482.x  1
2008 Bourke C, Deng K, Scott SD, Schapire RE, Vinodchandran NV. On reoptimizing multi-class classifiers Machine Learning. 71: 219-242. DOI: 10.1007/s10994-008-5056-8  1
2008 Freund Y, Schapire RE. Response to Mease and Wyner, evidence contrary to the statistical view of boosting, JMLR 9:131-156, 2008 Journal of Machine Learning Research. 9: 171-174.  1
2008 Syed U, Bowling M, Schapire RE. Apprenticeship learning using linear programming Proceedings of the 25th International Conference On Machine Learning. 1032-1039.  1
2007 Rudin C, Schapire RE, Daubechies I. Analysis of boosting algorithms using the smooth margin function Annals of Statistics. 35: 2723-2768. DOI: 10.1214/009053607000000785  1
2007 Dudik M, Blei DM, Schapire RE. Hierarchical maximum entropy density estimation Acm International Conference Proceeding Series. 227: 249-256. DOI: 10.1145/1273496.1273528  1
2007 Guisan A, Graham CH, Elith J, Huettmann F, Dudik M, Ferrier S, Hijmans R, Lehmann A, Li J, Lohmann LG, Loiselle B, Manion G, Moritz C, Nakamura M, Nakazawa Y, ... ... Schapire RE, et al. Sensitivity of predictive species distribution models to change in grain size Diversity and Distributions. 13: 332-340. DOI: 10.1111/j.1472-4642.2007.00342.x  1
2007 Syed U, Schapire RE. Imitation learning with a value-based prior Proceedings of the 23rd Conference On Uncertainty in Artificial Intelligence, Uai 2007. 384-391.  1
2007 Ortiz LE, Schapire RE, Kakade SM. Maximum entropy correlated equilibria Journal of Machine Learning Research. 2: 347-354.  1
2007 Dudík M, Phillips SJ, Schapire RE. Maximum entropy density estimation with generalized regularization and an application to species distribution modeling Journal of Machine Learning Research. 8: 1217-1260.  1
2006 Barutcuoglu Z, Schapire RE, Troyanskaya OG. Hierarchical multi-label prediction of gene function. Bioinformatics (Oxford, England). 22: 830-6. PMID 16410319 DOI: 10.1093/bioinformatics/btk048  1
2006 Reyzin L, Schapire RE. How boosting the margin can also boost classifier complexity Acm International Conference Proceeding Series. 148: 753-760. DOI: 10.1145/1143844.1143939  1
2006 Agarwal A, Hazan E, Kale S, Schapire RE. Algorithms for portfolio management based on the Newton method Acm International Conference Proceeding Series. 148: 9-16. DOI: 10.1145/1143844.1143846  1
2006 Phillips SJ, Anderson RP, Schapire RE. Maximum entropy modeling of species geographic distributions Ecological Modelling. 190: 231-259. DOI: 10.1016/j.ecolmodel.2005.03.026  1
2006 Dudík M, Schapire RE. Maximum entropy distribution estimation with generalized regularization Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 4005: 123-138.  1
2005 Schapire RE, Rochery M, Rahim M, Gupta N. Boosting with prior knowledge for call classification Ieee Transactions On Speech and Audio Processing. 13: 174-181. DOI: 10.1109/TSA.2004.840937  1
2005 Tur G, Hakkani-Tür D, Schapire RE. Combining active and semi-supervised learning for spoken language understanding Speech Communication. 45: 171-186. DOI: 10.1016/j.specom.2004.08.002  1
2005 Lozano AC, Kulkarni SR, Schapire RE. Convergence and consistency of regularized Boosting algorithms with stationary β-mixing observations Advances in Neural Information Processing Systems. 819-826.  1
2005 Dudík M, Schapire RE, Phillips SJ. Correcting sample selection bias in maximum entropy density estimation Advances in Neural Information Processing Systems. 323-330.  1
2005 Rudin C, Cortes C, Mohri M, Schapire RE. Margin-based ranking meets boosting in the middle Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 3559: 63-78.  1
2004 Freund Y, Mansour Y, Schapire RE. Generalization bounds for averaged classifiers Annals of Statistics. 32: 1698-1722. DOI: 10.1214/009053604000000058  1
2004 Freund Y, Iyer R, Schapire RE, Singer Y. An efficient boosting algorithm for combining preferences Journal of Machine Learning Research. 4: 933-969. DOI: 10.1162/1532443041827916  1
2004 Rudin C, Schapire RE, Daubechies I. Boosting based on a smooth margin Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science). 3120: 502-517.  1
2004 Rudin C, Daubechies I, Schapire RE. On the dynamics of boosting Advances in Neural Information Processing Systems 1
2004 Rudin C, Daubechies I, Schapire RE. The dynamics of AdaBoost: Cyclic behavior and convergence of margins Journal of Machine Learning Research. 5: 1557-1595.  1
2004 Phillips SJ, Dudík M, Schapire RE. A maximum entropy approach to species distribution modeling Proceedings, Twenty-First International Conference On Machine Learning, Icml 2004. 655-662.  1
2004 Dudik M, Phillips SJ, Schapire RE. Performance guarantees for regularized maximum entropy density estimation Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science). 3120: 472-486.  1
2003 Auer P, Cesa-Bianchi N, Freund Y, Schapire RE. The nonstochastic multiarmed bandit problem Siam Journal On Computing. 32: 48-77. DOI: 10.1137/S0097539701398375  1
2003 Tur G, Schapire RE, Hakkani-Tür D. Active learning for spoken language understanding Icassp, Ieee International Conference On Acoustics, Speech and Signal Processing - Proceedings. 1: 276-279.  1
2003 Stone P, Schapire RE, Littman ML, Csirik JA, McAllester D. Decision-theoretic bidding based on learned density Models in simultaneous, interacting auctions Journal of Artificial Intelligence Research. 19: 209-242.  1
2002 Collins M, Schapire RE, Singer Y. Logistic regression, AdaBoost and Bregman distances Machine Learning. 48: 253-285. DOI: 10.1023/A:1013912006537  1
2002 Collins M, Dasgupta S, Schapire RE. A generalization of principal component analysis to the exponential family Advances in Neural Information Processing Systems 1
2002 Stone P, Schapire RE, Csirik JA, Littman ML, McAllester D. ATTac-2001: A learning, autonomous bidding agent Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2531: 143-160.  1
2001 Schapire RE. Drifting games Machine Learning. 43: 265-291. DOI: 10.1023/A:1010800213066  1
2001 Allwein EL, Schapire RE, Singer Y. Reducing multiclass to binary: A unifying approach for margin classifiers Journal of Machine Learning Research. 1: 113-141.  1
2000 Schapire RE, Singer Y. BoosTexter: a boosting-based system for text categorization Machine Learning. 39: 135-168.  1
1999 Freund Y, Schapire RE. Large margin classification using the perceptron algorithm Machine Learning. 37: 277-296. DOI: 10.1023/A:1007662407062  1
1999 Schapire RE, Singer Y. Improved boosting algorithms using confidence-rated predictions Machine Learning. 37: 297-336. DOI: 10.1023/A:1007614523901  1
1999 Schapire RE. Theoretical views of boosting Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 1572: 1-10.  1
1999 Schapire RE. A brief introduction to boosting Ijcai International Joint Conference On Artificial Intelligence. 2: 1401-1406.  1
1999 Schapire RE. Theoretical, views of boosting and applications Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 1720: 13-25.  1
1999 Freund Y, Schapire RE. Adaptive Game Playing Using Multiplicative Weights Games and Economic Behavior. 29: 79-103.  1
1999 Cohen WW, Schapire RE, Singer Y. Learning to order things Journal of Artificial Intelligence Research. 10: 243-270.  1
1998 Helmbold DP, Schapire RE, Singer Y, Warmuth MK. On-line portfolio selection using multiplicative updates Mathematical Finance. 8: 325-347.  1
1998 Schapire RE, Freund Y, Bartlett P, Lee WS. Boosting the margin: A new explanation for the effectiveness of voting methods Annals of Statistics. 26: 1651-1686.  1
1997 Helmbold DP, Schapire RE. Predicting Nearly As Well As the Best Pruning of a Decision Tree Machine Learning. 27: 51-68.  1
1997 Helmbold DP, Schapire RE, Singer Y, Warmuth MK. A Comparison of New and Old Algorithms for a Mixture Estimation Problem Machine Learning. 27: 97-119.  1
1997 Cesa-Bianchi N, Freund Y, Haussler D, Helmbold DP, Schapire RE, Warmuth MK. How to use expert advice Journal of the Acm. 44: 427-485.  1
1997 Freund Y, Kearns M, Ron D, Rubinfeld R, Schapire RE, Sellie L. Efficient Learning of Typical Finite Automata from Random Walks Information and Computation. 138: 23-48.  1
1996 Schapire RE, Sellie LM. Learning sparse multivariate polynomials over a field with queries and counterexamples Journal of Computer and System Sciences. 52: 201-213. DOI: 10.1006/jcss.1996.0017  1
1996 Schapire RE. On the worst-case analysis of temporal-difference learning algorithms Machine Learning. 22: 95-121.  1
1995 Goldman SA, Kearns MJ, Schapire RE. On the Sample Complexity of Weak Learning Information and Computation. 117: 276-287. DOI: 10.1006/inco.1995.1045  1
1994 Rivest RL, Schapire RE. Diversity-Based Inference of Finite Automata Journal of the Acm (Jacm). 41: 555-589. DOI: 10.1145/176584.176589  1
1994 Haussler D, Kearns M, Schapire RE. Bounds on the Sample Complexity of Bayesian Learning Using Information Theory and the VC Dimension Machine Learning. 14: 83-113. DOI: 10.1023/A:1022698821832  1
1994 Schapire RE. Learning Probabilistic Read-once Formulas on Product Distributions Machine Learning. 14: 47-81. DOI: 10.1023/A:1022646704993  1
1994 Kearns MJ, Schapire RE, Sellie LM. Toward Efficient Agnostic Learning Machine Learning. 17: 115-141. DOI: 10.1023/A:1022615600103  1
1994 Kearns MJ, Schapire RE. Efficient distribution-free learning of probabilistic concepts Journal of Computer and System Sciences. 48: 464-497. DOI: 10.1016/S0022-0000(05)80062-5  1
1993 Rivest RL, Schapire RE. Inference of Finite Automata Using Homing Sequences Information and Computation. 103: 299-347. DOI: 10.1006/inco.1993.1021  1
1990 Schapire RE. The Strength of Weak Learnability Machine Learning. 5: 197-227. DOI: 10.1023/A:1022648800760  1
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