Abstract: In the realm of deep learning, the veracity and integrity of the training data are pivotal for constructing reliable and transparent models. This study introduces the concept of Trustworthy ...

Abstract: Data set bias not only compromises the fairness, accuracy and effectiveness of trained models, but also leads to a lower performance in real-world scenarios compared to the evaluation ...

Multiple reports show the data centers used to store, train and operate AI models use significant amounts of energy and water, with a rippling impact on the environment and public health. According to ...