The idea of the back propagation algorithm is to reduce this error, until the ANNs learns the training data. The training begins with random weights, and the goal is to adjust them so that the error will be minimal. This research evaluated the use of artificial neural networks (ANNs) ...
timely adaptation when optimal configuration changes, (ii) using minimum extra GPU computation, and (iii) doing so for a range of configuration knobs. To meet these requirements, we present OneAdapt, the first system that leverages the differentiability of DNNs to quickly adapt...
Usually, the effectiveness of an ML algorithm is highly dependent on the integrity of the input-data representation. It has been shown that a suitable data representation provides an improved performance when compared to a poor data representation. Thus, a significant research trend in ML for many...
The weights are initialized randomly and learned through the backpropagation algorithm. Convolutional Neural Network Get a complete overview of it through our blog Log Analytics with Machine Learning and Deep Learning. Modular Neural Network It is the combined structure of different types of it like ...
a concentration.The results showed that the Meiliang bay and centre of the lake Taihu respectively had average relative error of 71% and 39%,and the primary reasons of the poor predicing accuracy were hydrodynamic conditions,hydrometeorologicalin of Taihu Lake and factors of eco-system of algae....
Definition Provides information about the rate of change of a function with respect to its input variables An optimization algorithm is used to minimize (or maximize) a function by iteratively moving in the direction of the negative gradient Usage Give insights into the function’s behavior and dir...
introduced a highly efficient method for in situ training of an ONN. Figure 10c presents a schematic illustration of the proposed method, which uses adjoint variable methods to derive the photonic analog of the backpropagation algorithm127. The genetic algorithm was also demonstrated as an efficient...
we propose a multilayer backpropagation saliency detection algorithm based on depth mining by which we exploit depth cue from three different layers of images. The proposed algorithm shows a good performance and maintains the robustness in complex situations. Experiments’ results show that the proposed...
A random sample of 450 ... TB Patrick,JC Reid,ME Sievert,... - 《Proceedings of the American Society for Information Science & Technology》 被引量: 1发表: 2010年 加载更多 来源期刊 Journal of the Association for Information Science and Technology 1998-12-07 研究点推荐 Backpropagation ...
Zhang L, Gao T, Cai G, Hai KL (2022) Research on electric vehicle charging safety warning model based on back propagation neural network optimized by improved gray wolf algorithm. J Energy Storage. https://doi.org/10.1016/j.est.2022.104092 Article Google Scholar Wu X, Zheng W, Chen X,...