We first assign bias classes usingAge and Race attributes. Specifically, for theAge attribute, we divide samples into two groups; bias class 0 for samples withage 20and bias class 1for samples withage 10.

The diversity and dynamism of the real world require reinforcement learning (RL) agents that can quickly adapt and learn new behaviors when placed in novel situations.

Image super-resolution (SR) aims to reconstruct high-resolution (HR) images with more details from low-resolution (LR) images. Recently, deep learning-based image SR methods have made significant progress inreconstruction performance through deeper networkmodels andlarge-scale training datasets, but these improvements place higher demands on both computing power and memory resources, thus requiring more efficient solutions.