Abstract. Automatic pattern classifiers that allow for on-line incremental learning can adapt internal class models efficiently in response to new information without retraining fr...
In this paper, on-line training of neural networks is investigated in the context of computer-assisted colonoscopic diagnosis. A memory-based adaptation of the learning rate for t...
George D. Magoulas, Vassilis P. Plagianakos, Micha...
Despite the well-known performances and the theoretical power of neural networks, learning and generalizing are sometimes very difficult. In this article, we investigate how short ...
In Lp-spaces with p [1, ) there exists a best approximation mapping to the set of functions computable by Heaviside perceptron networks with n hidden units; however for p (1, ) ...
Abstract. One focus of recent research in the field of biologically plausible neural networks is the investigation of higher-level functions such as learning, development and modu...
Matthias Oster, Adrian M. Whatley, Shih-Chii Liu, ...