机译:最少的样本对浅神经网络的强大和资源有效识别
Department of Mathematics, TU München, Boltzmannstr. 3, D-85748 Garching bei München, Germany;
Department of Mathematics FNSPE, Czech Technical University in Prague, Trojanova 13, 12000 Prague, Czech Republic;
Department of Mathematics, Duke University, 120 Science Drive, Durham North Carolina 27708, USA;
Authentication; Orthogonal; FEEDFORWARDBleachingRobustnessSample pointrandomized algorithmsweight vectorsNeural networkuniform approximationTensor;
机译:[特别招待讲演] Role of optical technologies to create energy efficient transport networks
机译:[特别招待讲演] Role of optical technologies to create energy efficient transport networks
机译:Discussion of 'Maximum Gradient Decision-Making for Railways Based on Convolutional Neural Network' by Hao Pu, Hong Zhang, Paul Schonfeld, Wei Li, Jie Wang, Xianbao Peng, and Jianping Hu
机译:改进的CMAC神经网络非线性辨识算法(A Nonlinear Identification Algorithm of the Improved CMAC Neural Network)
机译:Learning Task-Oriented Dialog with Neural Network Methods =基于神经网络的任务型对话学习
机译:SpikingLab:由Netlogo中的Spiking Neural Networks控制的建模代理
机译:peak identification for pCDD/Fs in environmental samples at different temperature programs
机译:质量保证指导文件。质量保证项目计划:pm 2.5speciation Trends Network Field sampling