This paper presents Prio, a privacy-preserving system for the collection of aggregate
statistics. Each Prio client holds a private data value (eg, its current location), and a small set …

Ridge regression is an algorithm that takes as input a large number of data points and finds
the best-fit linear curve through these points. The algorithm is a building block for many …

Purpose One of the major hurdles in enabling personalized medicine is obtaining sufficient
patient data to feed into predictive models. Combining data originating from multiple …

Applications today rely on cloud databases for storing and querying time-series data. While
outsourcing storage is convenient, this data is often sensitive, making data breaches a …

Introduction The quantitative imaging features (radiomics) that can be obtained from the
different modalities of current-generation hybrid imaging can give complementary …

Federated Learning (FL) enables a large number of users to jointly learn a shared machine
learning (ML) model, coordinated by a centralized server, where the data is distributed …

Governments are under increasing pressure to publicly release collected data in order to
promote transparency, accountability, and innovation. Because much of the data they …

Recent advances to combine structured regression models and deep neural networks for
better interpretability, more expressiveness, and statistically valid uncertainty quantification …

Classical data mining algorithms implicitly assume complete access to all data, either in
centralized or federated form. However, privacy and security concerns often prevent sharing …

Data mining has emerged as a significant technology for gaining knowledge from vast
quantities of data. However, there has been growing concern that use of this technology is …