Tag: Data Privacy

Researchers at Lakehead University have built a federated spiking GAN that generates realistic synthetic EEG data for brain-computer interfaces while ...

A new conceptual framework proposes that primary schools could run small language models on low-cost local servers, keeping all student ...

Researchers have developed a revocable, time-based attribute-based encryption scheme for cloud-assisted IoT that cuts encryption and decryption times while saving ...

A newly released open-access R package called matrans makes parameter-transfer learning based on frequentist model averaging accessible for building cancer ...

Researchers have unveiled SENNA, a framework that combines disentangled semantic representations with large language models to generate synthetic tabular data ...

Researchers have developed two federated learning algorithms, Bi-Models Training and Multi-Models Training, that remove a client's influence from a shared ...

A new Cluster Computing study using stroke prediction shows that federated learning in healthcare will fail unless it confronts severe ...

A new federated learning framework called FedGPA balances global generalization and client personalization by aggregating neural network layers at different ...

An open specification and JSON schema called SLPT aims to make learner–AI interaction records portable and machine-checkable, while explicitly withholding ...

Researchers at Donghua University have developed RFLDefense, a layer-wise defense framework that suppresses backdoor attacks in federated learning even when ...