Generalized Regression with Conditional GANs

arXiv:2404.13500v1 Announce Type: new
Abstract: Regression is typically treated as a curve-fitting process where the goal is to fit a prediction function to data. With the help of conditional generative adversarial networks, we propose to solve this age-old problem in a different way; we aim to learn a prediction function whose outputs, when paired with the corresponding inputs, are indistinguishable from feature-label pairs in the training dataset. We show that this approach to regression makes fewer assumptions on the distribution …

arxiv cs.ai cs.lg gans generalized regression stat.ml type