When training classifiers, presence of noise can severely harm their performance. In this paper, we focus on “non-class” attribute noise and we consider how a frequent fault-t...
Image processing and recognition technologies are becoming increasingly important. Automatic construction methods for image transformation algorithms proposed to date approximate a...
Yuta Nakano, Shinichi Shirakawa, Noriko Yata, Tomo...
We present a framework for learning features for visual discrimination. The learning system is exposed to a sequence of training images. Whenever it fails to recognize a visual co...
Feature selection methods are often used to determine a small set of informative features that guarantee good classification results. Such procedures usually consist of two compon...
Artsiom Harol, Carmen Lai, Elzbieta Pekalska, Robe...
Temporal difference (TD) learning has been used to learn strong evaluation functions in a variety of two-player games. TD-gammon illustrated how the combination of game tree search...