A variety of explanation methods have been proposed in recent years to h...
Federated Learning (FL) is an approach to conduct machine learning witho...
A small subset of explainability techniques developed initially for imag...
Adversarial training (AT) has become a popular choice for training robus...
Saliency maps are a popular approach to creating post-hoc explanations o...
Federated learning distributes model training among a multitude of agent...
There is general consensus that it is important for artificial intellige...
Several researchers have argued that a machine learning system's
interpr...
Deep neural networks (DNNs) are vulnerable to adversarial examples, even...
Our ability to synthesize sensory data that preserves specific statistic...
Machine learning algorithms, in conjunction with user data, hold the pro...