With the rapid development of low-cost consumer electronics and pervasive adoption of next
generation wireless communication technologies, a tremendous amount of data has been …

Collecting and analyzing massive data generated from smart devices have become
increasingly pervasive in crowdsensing, which are the building blocks for data-driven …

As massive data are produced from small gadgets, federated learning on mobile devices
has become an emerging trend. In the federated setting, Stochastic Gradient Descent (SGD) …

Trajectory data has the potential to greatly benefit a wide-range of real-world applications,
such as tracking the spread of the disease through people's movement patterns and …

Differential privacy has been a de facto privacy standard in defining privacy and handling
privacy preservation. It has had great success in scenarios of local data privacy and …

With the advent of the era of big data, privacy issues have been becoming a hot topic in
public. Local differential privacy (LDP) is a state‐of‐the‐art privacy preservation technique …

As machine learning and artificial intelligence (ML/AI) are becoming more popular and
advanced, there is a wish to turn sensitive data into valuable information via ML/AI …

Sharing trajectories is beneficial for many real-world applications, such as managing
disease spread through contact tracing and tailoring public services to a population's travel …

Local Differential Privacy (LDP) provides provable privacy protection for data collection
without the assumption of the trusted data server. In the real-world scenario, different data …

This paper investigates the problem of collecting multidimensional data throughout time (ie,
longitudinal studies) for the fundamental task of frequency estimation under Local …