Federated learning (FL) is an emerging paradigm for distributed training...
Deep neural networks based object detection models have revolutionized
c...
This paper presents LDP-Fed, a novel federated learning system with a fo...
Federated learning (FL) is an emerging distributed machine learning fram...
The rapid growth of real-time huge data capturing has pushed the deep
le...
Federated Learning (FL) enables learning a shared model across many clie...
Membership inference attacks seek to infer the membership of individual
...
Deep neural network (DNN) has demonstrated its success in multiple domai...
Ensemble learning is a methodology that integrates multiple DNN learners...
Local Differential Privacy (LDP) is popularly used in practice for
priva...
Deep learning techniques based on neural networks have shown significant...
Training machine learning models often requires data from multiple parti...
The burgeoning success of deep learning has raised the security and priv...
Membership inference attacks seek to infer membership of individual trai...