167 citations · 458 across the 93 of their papers we have counts for
3 papers · 2 filters
Optimal Privacy Preserving for Federated Learning in Mobile Edge Computing
Hai M. Nguyen, Nam H. Chu, Diep N. Nguyen +5
Federated Learning (FL) with quantization and deliberately added noise over wireless networks is a promising approach to preserve user differential privacy (DP) while reducing wire…
Label driven Knowledge Distillation for Federated Learning with non-IID Data
Minh-Duong Nguyen, Quoc-Viet Pham, Dinh Thai Hoang +3
In real-world applications, Federated Learning (FL) meets two challenges: (1) scalability, especially when applied to massive IoT networks; and (2) how to be robust against an envi…
HCFL: A High Compression Approach for Communication-Efficient Federated Learning in Very Large Scale IoT Networks
Minh-Duong Nguyen, Sang-Min Lee, Quoc-Viet Pham +3
Federated learning (FL) is a new artificial intelligence concept that enables Internet-of-Things (IoT) devices to learn a collaborative model without sending the raw data to centra…