Nonparametric methods provide a flexible framework for estimating the probability density function of random variables without imposing a strict parametric model. By relying directly on observed data, ...

This study reports the findings of a comparison between different non-probability sampling methods applied in a WWW-user-survey. This study reports the findings of a comparison between different ...

What was the rationale behind applying machine learning (ML) models to improve identification probability in the absence of ...

Deep neural networks (DNNs) are demonstrated to be vulnerable to adversarial examples. Adversarial training is mainstrem ...