As patients are divided into ever more narrowly defined subgroups, the number of individuals available for research shrinks dramatically. While this approach improves personalization, it also creates ...

In an era where data breaches make headlines weekly and privacy regulations tighten globally, artificial intelligence faces a fundamental challenge: how to learn from data without compromising privacy ...

A collaborative approach to training AI models can yield better results, but it requires finding partners with data that complements your own. José Parra-Moyano, Karl Schmedders, and Maximilian Werner ...

Abstract: In this paper, we study the decentralized federated learning problem, which involves the collaborative training of a global model among multiple devices while ensuring data privacy. In ...

Each year, cyberattacks become more frequent and data breaches become more expensive. Whether companies seek to protect their AI system during development or use their algorithm to improve their ...

The reliance on public data — mostly web data — to train AI is holding back the AI field. That’s according to Daniel Beutel, a tech entrepreneur and researcher at the University of Cambridge, who ...

Jiaming Xu, an associate professor at Duke’s Fuqua School of Business says federated learning is a new approach that holds the promise of transforming Artificial Intelligence (AI) systems training. Xu ...

Although privacy-preserving technologies such as federated learning (FL) and differential privacy (DP) offer strong theoretical guarantees, it is not clear how such technologies actually perform under ...