A wide variety of machine learning problems can be described as minimizing a regularized risk functional, with different algorithms using different notions of risk and differen...
Choon Hui Teo, S. V. N. Vishwanathan, Alex J. Smol...
—Mass adoption of virtual world platforms for education and training implies efficient management of computational resources. In Second Life Grid and OpenSimulator, commonly used...
Andreas Vilela, Marcio Cardoso, Daniel Martins, Ar...
On large datasets, the popular training approach has been stochastic gradient descent (SGD). This paper proposes a modification of SGD, called averaged SGD with feedback (ASF), tha...
In this paper we studied re-sampling methods for learning classifiers from imbalanced data. We carried out a series of experiments on artificial data sets to explore the impact of ...
Krystyna Napierala, Jerzy Stefanowski, Szymon Wilk
Considering the wide range of possible behaviors to be acquired for domestic robots, applying a single learning method is clearly insufficient. In this paper, we propose a new str...