Many applications in multiagent learning are essentially convex optimization problems in which agents have only limited communication and partial information about the function be...
Renato L. G. Cavalcante, Alex Rogers, Nicholas R. ...
With the increase of the training set’s size, the efficiency of support vector machine (SVM) classifier will be confined. To solve such a problem, a novel preextracting method f...
Deqiang Han, Chongzhao Han, Yi Yang, Yu Liu, Wenta...
In this paper, we study an adaptive random search method based on continuous action-set learning automaton for solving stochastic optimization problems in which only the noisecorr...
In this paper, we propose an embedding method to seek an optimal low-dimensional manifold describing the intrinsical pose variations and to provide an identity-independent head pos...
We give an unified convergence analysis of ensemble learning methods including e.g. AdaBoost, Logistic Regression and the Least-SquareBoost algorithm for regression. These methods...