Tag: privacy-preserving machine learning

Researchers have developed a vertical federated deep learning framework using a binary manta ray optimization algorithm that selects cancer-related genes ...

Researchers have developed a differentially private stochastic gradient descent algorithm for outcome weighted learning that learns personalized treatment rules from ...

A new reinforcement learning framework called FLASH-DRM selects the most valuable devices for each federated learning round, improving accuracy, latency ...

A new federated learning framework lets hospitals train chest X-ray diagnostic AI collaboratively without sharing patient data, and it outperforms ...

Researchers have built a federated learning system that combines CKKS homomorphic encryption with blockchain storage, cutting adversarial attack success from ...

Researchers have developed GRAB-FL, a graph-aware federated learning framework that uses graph neural networks to assign trust scores to client ...

Researchers have unveiled a framework that trains personalized quantum classifiers across many users while each label is privatized locally, guaranteeing ...

Researchers have developed SWIFT-KD, a federated learning framework combining hierarchical sliding-window transformers with knowledge distillation that predicts building energy consumption ...

Millions of people who recovered from COVID-19 are discovering that the virus may have left behind an unwelcome souvenir: lasting ...

Artificial intelligence systems are increasingly trained on data that never leaves the devices where it is created—hospital servers holding sensitive ...