Abstract. The goal of this article is to introduce a collaborative clustering approach to the domain of ubiquitous knowledge discovery. This clustering approach is suitable in peer...
In this paper we propose an Rprop modification that builds on a mathematical framework for the convergence analysis to equip Rprop with a learning rates adaptation strategy that en...
Aristoklis D. Anastasiadis, George D. Magoulas, Mi...
We provide a worst-case analysis of selective sampling algorithms for learning linear threshold functions. The algorithms considered in this paper are Perceptron-like algorithms, ...
In this paper we present a method of parameter optimization, relative trust-region learning, where the trust-region method and the relative optimization [21] are jointly exploited...
Many algorithms in image analysis require a priority queue, a data structure that holds pointers to pixels in the image, and which allows efficiently finding the pixel in the queu...