Sanghoon Hong

Task Agnostic Robust Learning on Corrupt Outputs by Correlation-Guided Mixture Density Networks

In this paper, we focus on weakly supervised learning with noisy training data for both classification and regression problems. We assume that the training outputs are collected from a mixture of a target and correlated noise distributions. Our proposed method simultaneously estimates the target dis…