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ICML
2005
IEEE
16 years 2 months ago
Optimizing abstaining classifiers using ROC analysis
Classifiers that refrain from classification in certain cases can significantly reduce the misclassification cost. However, the parameters for such abstaining classifiers are ofte...
Tadeusz Pietraszek
COLT
2008
Springer
15 years 3 months ago
High-Probability Regret Bounds for Bandit Online Linear Optimization
We present a modification of the algorithm of Dani et al. [8] for the online linear optimization problem in the bandit setting, which with high probability has regret at most O ( ...
Peter L. Bartlett, Varsha Dani, Thomas P. Hayes, S...
COLT
2010
Springer
14 years 12 months ago
Active Learning on Trees and Graphs
We investigate the problem of active learning on a given tree whose nodes are assigned binary labels in an adversarial way. Inspired by recent results by Guillory and Bilmes, we c...
Nicolò Cesa-Bianchi, Claudio Gentile, Fabio...
ICML
2004
IEEE
16 years 2 months ago
Lookahead-based algorithms for anytime induction of decision trees
The majority of the existing algorithms for learning decision trees are greedy--a tree is induced top-down, making locally optimal decisions at each node. In most cases, however, ...
Saher Esmeir, Shaul Markovitch
121
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GECCO
2009
Springer
161views Optimization» more  GECCO 2009»
15 years 8 months ago
Are evolutionary rule learning algorithms appropriate for malware detection?
In this paper, we evaluate the performance of ten well-known evolutionary and non-evolutionary rule learning algorithms. The comparative study is performed on a real-world classiï...
M. Zubair Shafiq, S. Momina Tabish, Muddassar Faro...