Robust Estimation for Non-parametric Families via Generative Adversarial Networks
Robust Estimation for Non-parametric Families via Generative Adversarial Networks
We provide a general framework for designing Generative Adversarial Networks (GANs) to solve high-dimensional robust statistics problems, which aim at estimating unknown parameter of the true distribution given adversarially corrupted samples. Prior work [1], [2] focus on the problem of robust mean and covariance estimation when the true distribution lies …