Robert Schapire
Robert Schapire
Microsoft Research
Verified email at microsoft.com
Title
Cited by
Cited by
Year
A decision-theoretic generalization of on-line learning and an application to boosting
Y Freund, RE Schapire
Journal of computer and system sciences 55 (1), 119-139, 1997
198891997
Maximum entropy modeling of species geographic distributions
SJ Phillips, RP Anderson, RE Schapire
Ecological modelling 190 (3-4), 231-259, 2006
122772006
Experiments with a new boosting algorithm
Y Freund, RE Schapire
icml 96, 148-156, 1996
98001996
Novel methods improve prediction of species’ distributions from occurrence data
J Elith*, C H. Graham*, R P. Anderson, M Dudík, S Ferrier, A Guisan, ...
Ecography 29 (2), 129-151, 2006
71712006
The strength of weak learnability
RE Schapire
Machine learning 5 (2), 197-227, 1990
53661990
Improved boosting algorithms using confidence-rated predictions
RE Schapire, Y Singer
Machine learning 37 (3), 297-336, 1999
42761999
A short introduction to boosting
Y Freund, R Schapire, N Abe
Journal-Japanese Society For Artificial Intelligence 14 (771-780), 1612, 1999
37541999
Boosting the margin: A new explanation for the effectiveness of voting methods
RE Schapire, Y Freund, P Bartlett, WS Lee
The annals of statistics 26 (5), 1651-1686, 1998
32861998
BoosTexter: A boosting-based system for text categorization
RE Schapire, Y Singer
Machine learning 39 (2-3), 135-168, 2000
27632000
An efficient boosting algorithm for combining preferences
Y Freund, R Iyer, RE Schapire, Y Singer
Journal of machine learning research 4 (Nov), 933-969, 2003
24582003
Reducing multiclass to binary: A unifying approach for margin classifiers
EL Allwein, RE Schapire, Y Singer
Journal of machine learning research 1 (Dec), 113-141, 2000
22582000
Infogan: Interpretable representation learning by information maximizing generative adversarial nets
X Chen, Y Duan, R Houthooft, J Schulman, I Sutskever, P Abbeel
Advances in neural information processing systems, 2172-2180, 2016
21892016
The boosting approach to machine learning: An overview
RE Schapire
Nonlinear estimation and classification, 149-171, 2003
21712003
A maximum entropy approach to species distribution modeling
SJ Phillips, M Dudík, RE Schapire
Proceedings of the twenty-first international conference on Machine learning, 83, 2004
20982004
The nonstochastic multiarmed bandit problem
P Auer, N Cesa-Bianchi, Y Freund, RE Schapire
SIAM journal on computing 32 (1), 48-77, 2002
18362002
Large margin classification using the perceptron algorithm
Y Freund, RE Schapire
Machine learning 37 (3), 277-296, 1999
16221999
A contextual-bandit approach to personalized news article recommendation
L Li, W Chu, J Langford, RE Schapire
Proceedings of the 19th international conference on World wide web, 661-670, 2010
16022010
A brief introduction to boosting
RE Schapire
Ijcai 99, 1401-1406, 1999
14801999
Learning to order things
WW Cohen, RE Schapire, Y Singer
Advances in neural information processing systems, 451-457, 1998
10381998
How to use expert advice
N Cesa-Bianchi, Y Freund, D Haussler, DP Helmbold, RE Schapire, ...
Journal of the ACM (JACM) 44 (3), 427-485, 1997
8291997
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