Efficient Algorithms for Non-gaussian Single Index Models with Generative Priors
Efficient Algorithms for Non-gaussian Single Index Models with Generative Priors
In this work, we focus on high-dimensional single index models with non-Gaussian sensing vectors and generative priors. More specifically, our goal is to estimate the underlying signal from i.i.d. realizations of the semi-parameterized single index model, where the underlying signal is contained in (up to a constant scaling) the range …