research
∙
04/29/2023
FedGrad: Mitigating Backdoor Attacks in Federated Learning Through Local Ultimate Gradients Inspection
Federated learning (FL) enables multiple clients to train a model withou...
share
research
∙
02/21/2023
CADIS: Handling Cluster-skewed Non-IID Data in Federated Learning with Clustered Aggregation and Knowledge DIStilled Regularization
Federated learning enables edge devices to train a global model collabor...
research
∙
11/20/2022
FedDCT: Federated Learning of Large Convolutional Neural Networks on Resource Constrained Devices using Divide and Co-Training
We introduce FedDCT, a novel distributed learning paradigm that enables ...
research
∙
08/04/2022
FedDRL: Deep Reinforcement Learning-based Adaptive Aggregation for Non-IID Data in Federated Learning
The uneven distribution of local data across different edge devices (cli...
research
∙
04/19/2021
An Oracle for Guiding Large-Scale Model/Hybrid Parallel Training of Convolutional Neural Networks
Deep Neural Network (DNN) frameworks use distributed training to enable ...
research
∙
08/26/2020