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
206401997
Maximum entropy modeling of species geographic distributions
SJ Phillips, RP Anderson, RE Schapire
Ecological modelling 190 (3-4), 231-259, 2006
129382006
Experiments with a new boosting algorithm
Y Freund, RE Schapire
icml 96, 148-156, 1996
100711996
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
74412006
The strength of weak learnability
RE Schapire
Machine learning 5 (2), 197-227, 1990
55471990
Improved boosting algorithms using confidence-rated predictions
RE Schapire, Y Singer
Machine learning 37 (3), 297-336, 1999
43571999
A short introduction to boosting
Y Freund, R Schapire, N Abe
Journal-Japanese Society For Artificial Intelligence 14 (771-780), 1612, 1999
38971999
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
33731998
BoosTexter: A boosting-based system for text categorization
RE Schapire, Y Singer
Machine learning 39 (2-3), 135-168, 2000
28322000
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
25212003
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 29, 2172-2180, 2016
25102016
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
23132000
The boosting approach to machine learning: An overview
RE Schapire
Nonlinear estimation and classification, 149-171, 2003
22462003
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
22112004
The nonstochastic multiarmed bandit problem
P Auer, N Cesa-Bianchi, Y Freund, RE Schapire
SIAM journal on computing 32 (1), 48-77, 2002
19822002
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
17732010
Large margin classification using the perceptron algorithm
Y Freund, RE Schapire
Machine learning 37 (3), 277-296, 1999
16721999
A brief introduction to boosting
RE Schapire
Ijcai 99, 1401-1406, 1999
15321999
Learning to order things
WW Cohen, RE Schapire, Y Singer
Journal of artificial intelligence research 10, 243-270, 1999
10621999
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
8581997
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