Generative Adversarial Networks (GANs) have promoted a variety of applications in
computer vision and natural language processing, among others, due to its generative …

Cyber-Physical Systems (CPS) underpin global critical infrastructure, including power,
water, gas systems and smart grids. CPS, as a technology platform, is unique as a target for …

In this paper, we propose a new face de-identification method based on generative
adversarial network (GAN) to protect visual facial privacy, which is an end-to-end method …

Machine learning practitioners frequently seek to leverage the most informative available
data, without violating the data owner's privacy, when building predictive models …

The concerns on visual privacy have been increasingly raised along with the dramatic
growth in image and video capture and sharing. Meanwhile, with the recent breakthrough in …

The generalization capability of machine learning models, which refers to generalizing the
knowledge for an “unseen” domain via learning from one or multiple seen domain (s), is of …

The demand for the privacy-preserving survival analysis of medical data integrated from
multiple institutions or countries has been increased. However, sharing the original medical …

In cyber-physical systems, transforming a large amount of data collected from various
sensors onto informative low-dimension data is of paramount importance for efficient …

Driver maneuver interaction learning (DMIL) refers to the classification task with the goal of
identifying different driver-vehicle maneuver interactions (eg, left/right turns). Existing …

Multi-source data fusion, in which multiple data sources are jointly analyzed to obtain
improved information, has attracted considerable research attention. Data confidentiality and …