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COLT
2008
Springer
14 years 13 days 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...
LWA
2004
14 years 14 hour ago
A Simple Method For Estimating Conditional Probabilities For SVMs
Support Vector Machines (SVMs) have become a popular learning algorithm, in particular for large, high-dimensional classification problems. SVMs have been shown to give most accur...
Stefan Rüping
ICML
2010
IEEE
13 years 11 months ago
Risk minimization, probability elicitation, and cost-sensitive SVMs
A new procedure for learning cost-sensitive SVM classifiers is proposed. The SVM hinge loss is extended to the cost sensitive setting, and the cost-sensitive SVM is derived as the...
Hamed Masnadi-Shirazi, Nuno Vasconcelos
COLT
2004
Springer
14 years 4 months ago
Polynomial Time Prediction Strategy with Almost Optimal Mistake Probability
We give the first polynomial time prediction strategy for any PAC-learnable class C that probabilistically predicts the target with mistake probability poly(log(t)) t = ˜O 1 t w...
Nader H. Bshouty
ISIPTA
2005
IEEE
161views Mathematics» more  ISIPTA 2005»
14 years 4 months ago
Decision making under incomplete data using the imprecise Dirichlet model
The paper presents an efficient solution to decision problems where direct partial information on the distribution of the states of nature is available, either by observations of ...
Lev V. Utkin, Thomas Augustin