Kibok Lee

Robust Inference via Generative Classifiers for Handling Noisy Labels

2019 · arXiv (Cornell University)

Large-scale datasets may contain significant proportions of noisy (incorrect) class labels, and it is well-known that modern deep neural networks (DNNs) poorly generalize from such noisy training datasets. To mitigate the issue, we propose a …

A Simple Randomization Technique for Generalization in Deep Reinforcement Learning

2019 · arXiv (Cornell University)

Deep reinforcement learning (RL) agents often fail to generalize to unseen environments (yet semantically similar to trained agents), particularly when they are trained on high-dimensional state spaces, such as images. In this paper, we propose …