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 ...
Technology Networks

Federated AI Models Expand Access for Drug Discovery

A federated AI framework integrates predictive drug discovery models directly into a widely used research platform. The ...
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 ...
techtimes

The Future Of Federated Learning For User Privacy And Personalization

Digital personalization is demanded by customers in 2024, and going the extra mile for effective personalization is a key differentiating factor. In 2024, the demand for digital personalization ...
Forbes

Reinventing Anti-Money Laundering: How Federated Learning Can Power Fund Diversion Detection And GDPR Compliance

Danske Bank, Credit Suisse, Santander Bank UK, USAA Federal Savings Bank and Wells Fargo have all been subjected to significant fines, collectively amounting to about $2.2 billion, for various ...
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!

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 ...
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 ...