Using the Banach fixed-point theorem, we prove that activations close to zero mean and unit variance that are propagated through many network layers will converge towards zero mean and unit variance -- even under the presence of noise and perturbations. This convergence property of SNNs allows to...
原文链接:https://arxiv.org/abs/1908.07678 代码:https://github.com/MendelXu/ANN.git Non-local 是一种特别有用的语义分割技术,但也因其难以进行计算和占用GPU内存而受到批评。本文提出了Asymmetric Non-local Neural Network,其中有两个突出的组成部分:Asymmetric Pyramid N...2021...
We introduce DiPSeN, a Differentially Private Self-normalizing Neural Network which combines elements of differential privacy, self-normalization, and a novel optimization algorithm for adversarial client selection. Our empirical results on publicly available datasets for intrusion detection and image ...
Very deep CNNs achieve state-of-the-art results in both computer vision and speech recognition, but are difficult to train. The most popular way to train very deep CNNs is to use shortcut connections (SC) together with batch normalization (BN). Inspired by Self-Normalizing Neural Networks, ...
Here, we propose a new model for ESNs characterized by the use of a particular self-normalizing activation function that provides important features to the resulting network. Notably, the proposed activation function allows the network to exhibit nonlinear behaviors and, at the same time, provides ...
For the computer control system of the normalizeing furnace for the medium steel plate, the paper mentions its subsystem, roll way control, and proposes a algorithm used on it. This algorithm is based on the self-adjusting artificial neural network to optimize the PID parameter. By adopting the...
Despite various tricks and techniques thathave been employed to alleviate the problem in practice, there still lacks satisfactory theories or provablesolutions."Network Daily News
Echo state networkSelf-normalizing activationReservoir computingDeep ESNWe study prediction performance of Echo State Networks with multiple reservoirs built based on stacking and grouping. Grouping allows for developing independent subreservoir dynamics, which improves linear separability on readout layer. At...
A data-driven method for dynamic load forecasting of scraper conveyer based on rough set and multilayered self-normalizing gated recurrent networkHaitao HeZhengxiong LuChuanwei ZhangYuan WangWei GuoShuanfeng Zhao
First, DDC is proposed as a replacement for the conventional convolution operation in the Convolutional Neural Network (CNN) in order to cope with various shapes, sizes and arbitrary orientations of the objects. Second, SCAM embedded into the high layer of ReResNet-50, ...