AlphaGalileo

MLEDGE project proves federated learning can support real-world AI services

After two and a half years of work, the MLEDGE project (Cloud and Edge Machine Learning), led by Professor Nikolaos Laoutaris at IMDEA Networks, ...
American Banker

'Federated learning' can supercharge banks' AML detection

Not only can federated learning reduce costs, but it can also increase the effectiveness of anti-money-laundering, say Gary Shiffman, Shelly Liposky and Rick Hamilton. Financial institutions can help ...
InfoWorld

Federated learning: The killer use case for generative AI

Let’s imagine a fictional company, Global Retail Corporation, a multinational retail chain struggling with its initial approach to AI integration. They built custom generative AI applications on their ...
https//fedtechmagazine.com

How Federated Learning Helps Agencies Build Smarter AI Models Securely

Federated learning makes it possible for agency employees to collaborate on advanced artificial intelligence models without compromising data control or operational security. The process serves as a ...
VentureBeat

Major pharma companies, including Novartis and Merck, build federated learning platform for drug discovery

Join the event trusted by enterprise leaders for nearly two decades. VB Transform brings together the people building real enterprise AI strategy. Learn more Last June, 10 major pharmaceutical ...
GovCon Wire

Dell Technologies’ Ed Hicks: Federated Learning Could Help Agencies Advance AI at the Edge

Ed Hicks, business development manager for federal and artificial intelligence at Dell Technologies (NYSE: DELL), said government agencies that intend to implement AI at the edge should consider ...
EurekAlert!

A comprehensive survey of federated transfer learning: Challenges, methods and applications

Federated Learning (FL) has gained significant attention as a novel distributed machine learning paradigm that enables collaborative model training while preserving data privacy. However, traditional ...
EurekAlert!

Enhancing poisoning attack mitigation in federated learning through perturbation-defense complementarity on historical gradients

Federated Learning (FL) allows for privacy-preserving model training by enabling clients to upload model gradients without exposing their personal data. However, the decentralized nature of FL ...