Wethen develop an information rectification module (IRM) and a distribution guided distillation (DGD) scheme for fully quantized vision transformers (Q-ViT) to effectively eliminate such distortion, leading to a fully quantized ViTs.

We determine the sample complexity of pure exploration bandit problems with multiple goodanswers.

Diffusion models (DMs) have recently been introduced in image deblurring and exhibited promising performance, particularly in terms of details reconstruction.

Based on our framework, we also present a hybrid of DRL and EMalgorithms thathasaguaranteed convergencerate.

Inourexperiments, we visualize images for the mini-ImageNet dataset, and thus we utilize the image generator from the work [10] asG, which is pre-trained on ImageNet, and we pre-trainf on the mini-ImageNet dataset.