Synthetic data are becoming a critical tool for building artificially intelligent systems.
Simulators provide a way of generating data systematically and at scale. These data can …

Efficient compression of correlated data is essential to minimize communication overload in
multi-sensor networks. In such networks, each sensor independently compresses the data …

The unprecedented capture and application of face images raise increasing concerns on
anonymization to fight against privacy disclosure. Most existing methods may suffer from the …

Inference centers need more data to have a more comprehensive and beneficial learning
model, and for this purpose, they need to collect data from data providers. On the other …

Growing privacy concerns and regulations like GDPR and CCPA necessitate
pseudonymization techniques that protect identity in image datasets. However, retaining …

The growing richness of large-scale datasets has been crucial in driving the rapid
advancement and wide adoption of machine learning technologies. The massive collection …

With the advent of the multimedia era, the identification of sensitive information in social data
of online social network users has become critical for maintaining the security of network …

Critical decisions for large populations have conventionally been made top-down, with
million-dollar centralized satellites and surveillance tools used to sense events and …

To enhance the accuracy of learning models, it becomes imperative to train them on more
extensive datasets. Unfortunately, access to such data is often restricted because data …

The need for privacy makes data centers not provide their datasets to inference centers. On
the other hand, inference centers need more data to train learning algorithms and provide …