A state-of-the-art survey on solving non-iid data in federated learning
Federated Learning (FL) proposed in recent years has received significant attention from
researchers in that it can enable multiple clients to cooperatively train global models without …
researchers in that it can enable multiple clients to cooperatively train global models without …
Federated learning in edge computing: a systematic survey
Edge Computing (EC) is a new architecture that extends Cloud Computing (CC) services
closer to data sources. EC combined with Deep Learning (DL) is a promising technology …
closer to data sources. EC combined with Deep Learning (DL) is a promising technology …
[图书][B] Towards a standard for identifying and managing bias in artificial intelligence
R Schwartz, R Schwartz, A Vassilev, K Greene… - 2022 - dwt.com
As individuals and communities interact in and with an environment that is increasingly
virtual, they are often vulnerable to the commodification of their digital footprint. Concepts …
virtual, they are often vulnerable to the commodification of their digital footprint. Concepts …
Towards personalized federated learning
In parallel with the rapid adoption of artificial intelligence (AI) empowered by advances in AI
research, there has been growing awareness and concerns of data privacy. Recent …
research, there has been growing awareness and concerns of data privacy. Recent …
Layer-wised model aggregation for personalized federated learning
Abstract Personalized Federated Learning (pFL) not only can capture the common priors
from broad range of distributed data, but also support customized models for heterogeneous …
from broad range of distributed data, but also support customized models for heterogeneous …
Fedproto: Federated prototype learning across heterogeneous clients
Heterogeneity across clients in federated learning (FL) usually hinders the optimization
convergence and generalization performance when the aggregation of clients' knowledge …
convergence and generalization performance when the aggregation of clients' knowledge …
Privacy and robustness in federated learning: Attacks and defenses
As data are increasingly being stored in different silos and societies becoming more aware
of data privacy issues, the traditional centralized training of artificial intelligence (AI) models …
of data privacy issues, the traditional centralized training of artificial intelligence (AI) models …
Blockchain-enabled federated learning: A survey
Federated learning (FL) has experienced a boom in recent years, which is jointly promoted
by the prosperity of machine learning and Artificial Intelligence along with emerging privacy …
by the prosperity of machine learning and Artificial Intelligence along with emerging privacy …
Data heterogeneity-robust federated learning via group client selection in industrial IoT
Nowadays, the Industrial Internet of Things (IIoT) has played an integral role in Industry 4.0
and produced massive amounts of data for industrial intelligence. These data locate on …
and produced massive amounts of data for industrial intelligence. These data locate on …
Level-5 autonomous driving—are we there yet? a review of research literature
Autonomous vehicles are revolutionizing transport and next-generation autonomous
mobility. Such vehicles are promising to increase road safety, improve traffic efficiency …
mobility. Such vehicles are promising to increase road safety, improve traffic efficiency …