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Error analysis of generative adversarial network
In this research, we focus on studying the error convergence rate of the GAN model that is based on a class of functions encompassing the discriminator and generator neural networks.
Nonparametric regression with modified ReLU networks
We consider regression estimation with modified ReLU neural networks in which network weight matrices are first modified by a function $\alpha$ before being multiplied by input vectors.
A Statistician Teaches Deep Learning
Deep learning (DL) has gained much attention and become increasingly popular in modern data science.
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