论文标题
关于回归问题中深度复发性神经网络估计的收敛速度与依赖数据
On the rate of convergence of a deep recurrent neural network estimate in a regression problem with dependent data
论文作者
论文摘要
考虑了与依赖数据的回归问题。引入了对数据依赖性的规律性假设，并表明在回归函数的适当结构假设下，深度复发的神经网络估计能够避免维数的诅咒。
A regression problem with dependent data is considered. Regularity assumptions on the dependency of the data are introduced, and it is shown that under suitable structural assumptions on the regression function a deep recurrent neural network estimate is able to circumvent the curse of dimensionality.
