Learning optimal discriminant functions through a cooperative game of automata
IEEE Transactions on Systems, Man and Cybernetics
Learning automata: an introduction
Learning automata: an introduction
Robust trainability of single neurons
COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
Learning linear threshold functions in the presence of classification noise
COLT '94 Proceedings of the seventh annual conference on Computational learning theory
Efficient noise-tolerant learning from statistical queries
Journal of the ACM (JACM)
An introduction to support Vector Machines: and other kernel-based learning methods
An introduction to support Vector Machines: and other kernel-based learning methods
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning Automata and Stochastic Optimization
Learning Automata and Stochastic Optimization
A polynomial-time algorithm for learning noisy linear threshold functions
FOCS '96 Proceedings of the 37th Annual Symposium on Foundations of Computer Science
Pruning Training Sets for Learning of Object Categories
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
A Boosting Approach to remove Class Label Noise
HIS '05 Proceedings of the Fifth International Conference on Hybrid Intelligent Systems
Networks of Learning Automata: Techniques for Online Stochastic Optimization
Networks of Learning Automata: Techniques for Online Stochastic Optimization
Noise Tolerant Variants of the Perceptron Algorithm
The Journal of Machine Learning Research
Robust support vector machine training via convex outlier ablation
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
An adaptive call admission algorithm for cellular networks
Computers and Electrical Engineering
Varieties of learning automata: an overview
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
On the use of learning automata in the control of broadcast networks: a methodology
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Learning automata based dynamic guard channel algorithms
Computers and Electrical Engineering
Function optimisation by learning automata
Information Sciences: an International Journal
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Learning automata are adaptive decision making devices that are found useful in a variety of machine learning and pattern recognition applications. Although most learning automata methods deal with the case of finitely many actions for the automaton, there are also models of continuous-action-set learning automata (CALA). A team of such CALA can be useful in stochastic optimization problems where one has access only to noise-corrupted values of the objective function. In this paper, we present a novel formulation for noise-tolerant learning of linear classifiers using a CALA team. We consider the general case of nonuniform noise, where the probability that the class label of an example is wrong may be a function of the feature vector of the example. The objective is to learn the underlying separating hyperplane given only such noisy examples.We present an algorithm employing a team of CALA and prove, under some conditions on the class conditional densities, that the algorithm achieves noise-tolerant learning as long as the probability of wrong label for any example is less than 0.5. We also present some empirical results to illustrate the effectiveness of the algorithm.