Beyond the Edge: An Advanced Exploration of Reinforcement Learning for Mobile Edge Computing, its Applications, and Future Research Trajectories
Mobile Edge Computing (MEC) broadens the scope of computation and storage beyond the
central network, incorporating edge nodes close to end devices. This expansion facilitates …
central network, incorporating edge nodes close to end devices. This expansion facilitates …
PAGE: Equilibrate Personalization and Generalization in Federated Learning
Federated learning (FL) is becoming a major driving force behind machine learning as a
service, where customers (clients) collaboratively benefit from shared local updates under …
service, where customers (clients) collaboratively benefit from shared local updates under …
A Multifaceted Survey on Federated Learning: Fundamentals, Paradigm Shifts, Practical Issues, Recent Developments, Partnerships, Trade-Offs, Trustworthiness, and …
A Majeed, SO Hwang - IEEE Access, 2024 - ieeexplore.ieee.org
Federated learning (FL) is considered a de facto standard for privacy preservation in AI
environments because it does not require data to be aggregated in some central place to …
environments because it does not require data to be aggregated in some central place to …
Prototype Similarity Distillation for Communication-Efficient Federated Unsupervised Representation Learning
C Zhang, Y Xie, T Chen, W Mao… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Federated unsupervised representation learning aims at leveraging unlabeled data from
multiple parties to learn visual representations without compromising the data privacy and …
multiple parties to learn visual representations without compromising the data privacy and …
QP-LDP for better global model performance in federated learning
Federated learning (FL) enhanced by local differential privacy (LDP) has gained promising
privacy-preserving capabilities against privacy attacks on local contributions. In this context …
privacy-preserving capabilities against privacy attacks on local contributions. In this context …
Federated Learning Survey: A Multi-Level Taxonomy of Aggregation Techniques, Experimental Insights, and Future Frontiers
The emerging integration of IoT (Internet of Things) and AI (Artificial Intelligence) has
unlocked numerous opportunities for innovation across diverse industries. However …
unlocked numerous opportunities for innovation across diverse industries. However …
Basalt: Server-Client Joint Defense Mechanism for Byzantine-Robust Federated Learning
Federated Learning, a distributed machine learning paradigm, is susceptible to Byzantine
attacks since the attacker can manipulate clients' local data and models to compromise the …
attacks since the attacker can manipulate clients' local data and models to compromise the …
FSSA: Efficient 3-Round Secure Aggregation for Privacy-Preserving Federated Learning
Federated learning (FL) allows a large number of clients to collaboratively train machine
learning (ML) models by sending only their local gradients to a central server for …
learning (ML) models by sending only their local gradients to a central server for …