-
1
-
-
84954269292
-
-
http://metaoptimize.com/qa/questions/1885/supposeyour-training-and-test-set-are-generated-by-a-cunningadversary, 2010.
-
(2010)
-
-
-
2
-
-
0003924391
-
-
Cambridge University Press, New York, NY, USA, 1st edition
-
Martin Anthony and Peter L. Bartlett. Neural Network Learning: Theoretical Foundations. Cambridge University Press, New York, NY, USA, 1st edition, 2009.
-
(2009)
Neural Network Learning: Theoretical Foundations
-
-
Anthony, M.1
Bartlett, P.L.2
-
3
-
-
0032645080
-
An empirical comparison of voting classification algorithms: Bagging, boosting, and variants
-
Eric Bauer and Ron Kohavi. An empirical comparison of voting classification algorithms: Bagging, boosting, and variants. Machine Learning, 36(1-2), 1999.
-
(1999)
Machine Learning
, vol.36
, Issue.1-2
-
-
Bauer, E.1
Kohavi, R.2
-
5
-
-
71149102767
-
Robust bounds for classification via selective sampling
-
Montreal, Canada
-
Nicolo Cesa-Bianchi, Claudio Gentile, and Francesco Orabona. Robust bounds for classification via selective sampling. In ICML, Montreal, Canada, 2009.
-
(2009)
ICML
-
-
Cesa-Bianchi, N.1
Gentile, C.2
Orabona, F.3
-
6
-
-
85127836544
-
Discriminative training methods for hidden markov models: Theory and experiments with per-ceptron algorithms
-
Stroudsburg, USA
-
Michael Collins. Discriminative training methods for hidden markov models: theory and experiments with per-ceptron algorithms. In EMNLP, Stroudsburg, USA, 2002.
-
(2002)
EMNLP
-
-
Collins, M.1
-
7
-
-
84875634609
-
Robust selective sampling from single and multiple teachers
-
Haifa, Israel
-
Ofer Dekel, Claudio Gentile, and Karthik Sridharan. Robust selective sampling from single and multiple teachers. In COLT, Haifa, Israel, 2010.
-
(2010)
COLT
-
-
Dekel, O.1
Gentile, C.2
Sridharan, K.3
-
8
-
-
0029521676
-
Sample compression, learnability, and the vapnik-chervonenkis dimension
-
Sally Floyd and Manfred Warmuth. Sample compression, learnability, and the vapnik-chervonenkis dimension. Machine Learning, 50:269-304, 1995.
-
(1995)
Machine Learning
, vol.50
, pp. 269-304
-
-
Floyd, S.1
Warmuth, M.2
-
14
-
-
78049528115
-
Machine learning in adversarial environments
-
Pavel Laskov and Richard Lippmann. Machine learning in adversarial environments. Machine Learning, 81(2), 2010.
-
(2010)
Machine Learning
, vol.81
, pp. 2
-
-
Laskov, P.1
Lippmann, R.2
-
15
-
-
0035789273
-
The distributed boosting algorithm
-
San Francisco, USA
-
Aleksandar Lazarevic and Zoran Obradovic. The distributed boosting algorithm. In KDD, San Francisco, USA, 2001.
-
(2001)
KDD
-
-
Lazarevic, A.1
Obradovic, Z.2
-
16
-
-
80052652249
-
Efficient large-scale distributed training of conditional maximum entropy models
-
Vancouver, Canada
-
Gideon Mann, Ryan McDonald, Mehryar Mohri, Nathan Silberman, and Dan Walker. Efficient large-scale distributed training of conditional maximum entropy models. In NIPS, Vancouver, Canada, 2009.
-
(2009)
NIPS
-
-
Mann, G.1
McDonald, R.2
Mohri, M.3
Silberman, N.4
Walker, D.5
-
17
-
-
80052650170
-
Distributed training strategies for the structured perceptron
-
Los Angeles, California
-
Ryan McDonald, Keith Hall, and Gideon Mann. Distributed training strategies for the structured perceptron. In NAACL HLT, Los Angeles, California, 2010.
-
(2010)
NAACL HLT
-
-
McDonald, R.1
Hall, K.2
Mann, G.3
-
19
-
-
68949137209
-
Active learning literature survey
-
University of Wisconsin-Madison
-
Burr Settles. Active learning literature survey. In Computer Sciences Technical Report 1648, University of Wisconsin-Madison, 2009.
-
(2009)
Computer Sciences Technical Report
, vol.1648
-
-
Settles, B.1
|