— Numerical condition affects the learning speed and accuracy of most artificial neural network learning algorithms. In this paper, we examine the influence of opposite transfe...
We present several modifications of the original recurrent neural network language model (RNN LM). While this model has been shown to significantly outperform many competitive l...
Tomas Mikolov, Stefan Kombrink, Lukas Burget, Jan ...
— Representation of knowledge within a neural model is an active field of research involved with the development of alternative structures, training algorithms, learning modes an...
Image denoising can be described as the problem of mapping from a noisy image to a noise-free image. The best currently available denoising methods approximate this mapping with c...
Harold Christopher Burger, Christian J. Schuler, S...
This paper presents a novel approach for detecting network intrusions based on a competitive learning neural network. In the paper, the performance of this approach is compared to...