Algorithmic fairness in artificial intelligence for medicine and healthcare
In healthcare, the development and deployment of insufficiently fair systems of artificial
intelligence (AI) can undermine the delivery of equitable care. Assessments of AI models …
intelligence (AI) can undermine the delivery of equitable care. Assessments of AI models …
[HTML][HTML] Federated learning for 6G-enabled secure communication systems: a comprehensive survey
Abstract Machine learning (ML) and Deep learning (DL) models are popular in many areas,
from business, medicine, industries, healthcare, transportation, smart cities, and many more …
from business, medicine, industries, healthcare, transportation, smart cities, and many more …
Fedgan-ids: Privacy-preserving ids using gan and federated learning
Federated Learning (FL) is a promising distributed training model that aims to minimize the
data sharing to enhance privacy and performance. FL requires sufficient and diverse training …
data sharing to enhance privacy and performance. FL requires sufficient and diverse training …
Dafkd: Domain-aware federated knowledge distillation
Federated Distillation (FD) has recently attracted increasing attention for its efficiency in
aggregating multiple diverse local models trained from statistically heterogeneous data of …
aggregating multiple diverse local models trained from statistically heterogeneous data of …
PerFED-GAN: Personalized federated learning via generative adversarial networks
Federated learning is gaining popularity as a distributed machine learning method that can
be used to deploy AI-dependent Internet of Things applications while protecting client data …
be used to deploy AI-dependent Internet of Things applications while protecting client data …
Cgan-based collaborative intrusion detection for uav networks: A blockchain-empowered distributed federated learning approach
X He, Q Chen, L Tang, W Wang… - IEEE Internet of Things …, 2022 - ieeexplore.ieee.org
Numerous resource-constrained Internet of Things (IoT) devices make the edge IoT
consisting of unmanned aerial vehicles (UAVs) vulnerable to network intrusion. Therefore, it …
consisting of unmanned aerial vehicles (UAVs) vulnerable to network intrusion. Therefore, it …
Comprehensive analysis of privacy leakage in vertical federated learning during prediction
X Jiang, X Zhou, J Grossklags - Proceedings on Privacy …, 2022 - petsymposium.org
Vertical federated learning (VFL), a variant of federated learning, has recently attracted
increasing attention. An active party having the true labels jointly trains a model with other …
increasing attention. An active party having the true labels jointly trains a model with other …
Federated generative model on multi-source heterogeneous data in iot
The study of generative models is a promising branch of deep learning techniques, which
has been successfully applied to different scenarios, such as Artificial Intelligence and the …
has been successfully applied to different scenarios, such as Artificial Intelligence and the …
Algorithm fairness in ai for medicine and healthcare
In the current development and deployment of many artificial intelligence (AI) systems in
healthcare, algorithm fairness is a challenging problem in delivering equitable care. Recent …
healthcare, algorithm fairness is a challenging problem in delivering equitable care. Recent …
Towards data-independent knowledge transfer in model-heterogeneous federated learning
Federated Distillation (FD) extends classic Federated Learning (FL) to a more general
training framework that enables model-heterogeneous collaborative learning by Knowledge …
training framework that enables model-heterogeneous collaborative learning by Knowledge …