409 citations · 626 across the 7 of their papers we have counts for
7 papers
Federated Deep Reinforcement Learning-based Bitrate Adaptation for Dynamic Adaptive Streaming over HTTP
Phuong L. Vo, Nghia T. Nguyen, Long Luu +3
In video streaming over HTTP, the bitrate adaptation selects the quality of video chunks depending on the current network condition. Some previous works have applied deep reinforce…
On the Generalization of Wasserstein Robust Federated Learning
Tung-Anh Nguyen, Tuan Dung Nguyen, Long Tan Le +2
In federated learning, participating clients typically possess non-i.i.d. data, posing a significant challenge to generalization to unseen distributions. To address this, we propos…
Channel Estimation in RIS-assisted Downlink Massive MIMO: A Learning-Based Approach
Tung T. Vu, Trinh Van Chien, Canh T. Dinh +2
For downlink massive multiple-input multiple-output (MIMO) operating in time-division duplex protocol, users can decode the signals effectively by only utilizing the channel statis…
A New Look and Convergence Rate of Federated Multi-Task Learning with Laplacian Regularization
Canh T. Dinh, Tung T. Vu, Nguyen H. Tran +2
Non-Independent and Identically Distributed (non- IID) data distribution among clients is considered as the key factor that degrades the performance of federated learning (FL). Sev…
DONE: Distributed Approximate Newton-type Method for Federated Edge Learning
Canh T. Dinh, Nguyen H. Tran, Tuan Dung Nguyen +4
There is growing interest in applying distributed machine learning to edge computing, forming federated edge learning. Federated edge learning faces non-i.i.d. and heterogeneous da…
Personalized Federated Learning with Moreau Envelopes
Canh T. Dinh, Nguyen H. Tran, Tuan Dung Nguyen
Federated learning (FL) is a decentralized and privacy-preserving machine learning technique in which a group of clients collaborate with a server to learn a global model without s…
Federated Learning over Wireless Networks: Convergence Analysis and Resource Allocation
Canh T. Dinh, Nguyen H. Tran, Minh N. H. Nguyen +4
There is an increasing interest in a fast-growing machine learning technique called Federated Learning, in which the model training is distributed over mobile user equipments (UEs)…