Feb 2, 2022 · Abstract:We provide a general framework for designing Generative Adversarial Networks (GANs) to solve high dimensional robust statistics ...
Abstract—We provide a general framework for designing Gen- erative Adversarial Networks (GANs) to solve high-dimensional robust statistics problems, which ...
This work provides a general framework for designing Generative Adversarial Networks (GANs) to solve high-dimensional robust statistics problems, ...
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We provide a general framework for designing Generative Adversarial Networks (GANs) to solve high dimensional robust statistics problems, ...
Jun 28, 2022 · “Robust. Estimation for Nonparametric Families via Generative Adversarial. Networks.” In: arXiv preprint arXiv:2202.01269. Zhu, Banghua ...
In this paper, we propose a ... [Show full abstract] robust adaptive estimation algorithm for networks with cyclic cooperation. We model the impulsive noise as ...
In this paper , the authors provide a general framework for designing GANs to solve high dimensional robust statistics problems, which aim at estimating unknown ...
Dec 20, 2018 · This connection opens the door of computing robust estimators using tools developed for training GANs. In particular, we show that a JS-GAN that ...
It is shown in both theory and experiments that some appropriate structures of discriminator networks with hidden layers in GANs lead to statistically ...
This framework allows us to understand both matrix depth function, a technique of rate- optimal robust estimation, and various GANs through the lens of ...