Robert E. Schapire

Robert E. Schapire is a person.

• See: AdaBoost Algorithm, Yoav Freund.

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References

• http://www.cs.princeton.edu/~schapire/

2010

• (Li et al., 2010) ⇒ Lihong Li, Wei Chu, John Langford, and Robert E. Schapire. (2010). “A Contextual-bandit Approach to Personalized News Article Recommendation.” In: Proceedings of the 19th International Conference on World wide web. doi:10.1145/1772690.1772758

2005

• (Langford & Schapire, 2005) ⇒ John Langford, and Robert Schapire. “Tutorial on Practical Prediction Theory for Classification.” In: Journal of machine learning research 6, no. 3 (2005).

2004

• (Tur et al., 2004) ⇒ Gokhan Tur, Dilek Hakkani-Tür, and Robert E. Schapire. (2004). “Combining active and semi-supervised learning for spoken language understanding.” doi:10.1016/j.specom.2004.08.002

2003

• (Auer et al., 2003) ⇒ Peter Auer, Nicolò Cesa-Bianchi, Yoav Freund, and Robert E. Schapire. (2003). “The Nonstochastic Multiarmed Bandit Problem.” In: SIAM Journal on Computing, 32(1). doi:10.1137/S0097539701398375

2001

• (Allwein et al., 2001) ⇒ Erin L. Allwein, Robert E. Schapire, and Yoram Singer. (2001). “Reducing Multiclass to Binary: a unifying approach for margin classifiers.” In: The Journal of Machine Learning Research, 1. doi:10.1162/15324430152733133

2000

• (Collins et al., 2000) ⇒ Michael Collins, Robert E. Schapire, and Yoram Singer. (2000). “Logistic Regression, AdaBoost, and Bregman distances. Proceedings of 13th COLT. scaling for log-linear models. The Annals of Mathematical Statistics, 43, 1470–1480.
• (Schapire & Singer, 2000) ⇒ Robert E. Schapire, and Yoram Singer. (2002). “BoosTexter: A Boosting-based System for Text Categorization.” In: Machine Learning, 39(2/3).

1999

• (Abney et al., 1999) ⇒ Steven P. Abney, Robert E. Schapire, and Yoram Singer. (1999). “Boosting Applied to Tagging and PP Attachment.” In: Proceedings of SIGDAT ACL Conference on EMNLPVLC.
• (Freund & Schapire, 1999) ⇒ Yoav Freund, and Robert E. Schapire. (1999). “Large Margin Classification Using the Perceptron Algorithm.” In: Machine Learning, 37(3). doi:10.1023/A:1007662407062.

1998

• (Freund & Schapire, 1998) ⇒ Yoav Freund, and Robert E. Schapire. (1998). “Large Margin Classification Using the Perceptron Algorithm.” In: Proceedings of the eleventh annual conference on Computational learning theory doi:10.1145/279943.279985
• (Schapire et al., 1998) ⇒ Robert E. Schapire, Yoav Freund, Peter L. Bartlett, and Wee Sun Lee. (1998). “Boosting the Margin: A new explanation for the effectiveness of voting methods.” In: The Annals of Statistics, 26(5). http://www.jstor.org/stable/120016
• (Schapire & Singer, 1998) ⇒ Robert E. Schapire and Yoram Singer. (1998). “Improved Boosting Algorithms Using Confidence-Rated Predictions.” In: Proceeings of 11th Ann. Conference Computational Learning Theory (COLT 1998).

1997

• (Freund & Schapire, 1997) ⇒ Yoav Freund, and Robert E. Schapire (1997). “A Decision-Theoretic Generalization of On-line Learning and an Application to Boosting.” In: Journal of Computer and System Sciences, 55(1).

1996

• (Freund & Schapire, 1996) ⇒ Yoav Freund, and Robert E. Schapire. (1996). “Experiments with a New Boosting Algorithm.” In: Proceedings of the Thirteenth International Conference on Machine Learning (ICML 1996).
• (Lewis et al., 1996) ⇒ David D. Lewis, Robert E. Schapire, James P. Callan, and Ron Papka. (1996). “Training Algorithms for Linear Text Classifiers.” In: Proceedings of the ACM SIGIR Conference (SIGIR 1996).

1990

• (Schapire, 1990) ⇒ Robert E. Schapire. (1990). “The Strength of Weak Learnability.” In: Machine Learning, 5(2).

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