Learning object categories from small samples is a challenging problem, where machine learning tools can in general provide very few guarantees. Exploiting prior knowledge may be ...
Tatiana Tommasi, Francesco Orabona, Barbara Caputo
Abstract. This paper presents the overall system of a learning, selforganizing, and adaptive controller used to optimize the combustion process in a hard-coal fired power plant. T...
Erik Schaffernicht, Volker Stephan, Klaus Debes, H...
The small sample size problem and the difficulty in determining the optimal reduced dimension limit the application of subspace learning methods in the gait recognition domain. To...
—In increasingly many cases of interest in computer vision and pattern recognition, one is often confronted with the situation where data size is very large. Usually, the labels ...
Genetic Programming uses trees to represent chromosomes. The user defines the representation space by defining the set of functions and terminals to label the nodes in the trees. ...