695 search results - page 5 / 139 » Efficient Algorithms for General Active Learning |
ICML
2009
IEEE
14 years 8 months ago
2009
IEEE
We propose an importance weighting framework for actively labeling samples. This technique yields practical yet sound active learning algorithms for general loss functions. Experi...
COLT
2005
Springer
14 years 1 months ago
2005
Springer
We start by showing that in an active learning setting, the Perceptron algorithm needs Ω( 1 ε2 ) labels to learn linear separators within generalization error ε. We then prese...
EMNLP
2009
13 years 5 months ago
2009
Methods that learn from prior information about input features such as generalized expectation (GE) have been used to train accurate models with very little effort. In this paper,...
PKDD
2009
Springer
14 years 4 days ago
2009
Springer
Abstract. This paper focuses on Active Learning with a limited number of queries; in application domains such as Numerical Engineering, the size of the training set might be limite...
PKDD
2009
Springer
14 years 2 months ago
2009
Springer
Abstract. Inverse reinforcement learning addresses the general problem of recovering a reward function from samples of a policy provided by an expert/demonstrator. In this paper, w...