Visual Prompt Tuning (VPT) is an effective tuning method for adapting
pr...
Interpretable models are designed to make decisions in a human-interpret...
Imitation learning, in which learning is performed by demonstration, has...
The aim of continual learning is to learn new tasks continuously (i.e.,
...
Personalized federated learning is aimed at allowing numerous clients to...
Source-free unsupervised domain adaptation (SFUDA) aims to obtain high
p...
Generative adversarial networks (GANs) with clustered latent spaces can
...
We propose an interpretable Capsule Network, iCaps, for image classifica...
It is difficult to detect and remove secret images that are hidden in na...
Most deep learning classification studies assume clean data. However, di...
Typical personal medical data contains sensitive information about
indiv...
Steganography is the science of unnoticeably concealing a secret message...
With the development of machine learning, expectations for artificial
in...