In this paper we address the problem of classifying images, by exploiting global features that describe color and illumination properties, and by using the statistical learning pa...
Boosting algorithms like AdaBoost and Arc-GV are iterative strategies to minimize a constrained objective function, equivalent to Barrier algorithms. Based on this new understandi...
This paper introduces a new method using dyadic decision trees for estimating a classification or a regression function in a multiclass classification problem. The estimator is bas...
In this paper, we motivate the need for and challenges involved in supporting imprecise queries over Web databases. Then we briefly explain our solution, AIMQ - a domain independe...
In this paper, an architecture of a resourceallocating learning probabilistic neural network is considered. Construction and learning algorithms are proposed. The advantages of th...