Search Results for author: Minh N. Dao

Found 4 papers, 3 papers with code

Graph Augmentation Learning

1 code implementation17 Mar 2022 Shuo Yu, Huafei Huang, Minh N. Dao, Feng Xia

To better show the outperformance of GAL, we experimentally validate the effectiveness and adaptability of different GAL strategies in different downstream tasks.

Graph Learning

A New Look and Convergence Rate of Federated Multi-Task Learning with Laplacian Regularization

2 code implementations14 Feb 2021 Canh T. Dinh, Tung T. Vu, Nguyen H. Tran, Minh N. Dao, Hongyu Zhang

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).

Few-Shot Learning Multi-Task Learning +1

Joint Resource Allocation to Minimize Execution Time of Federated Learning in Cell-Free Massive MIMO

1 code implementation4 Sep 2020 Tung T. Vu, Duy T. Ngo, Hien Quoc Ngo, Minh N. Dao, Nguyen H. Tran, Richard H. Middleton

We then develop a new algorithm that is proven to converge to the neighbourhood of the stationary points of the formulated problem.

Information Theory Information Theory

Cell-Free Massive MIMO for Wireless Federated Learning

no code implementations27 Sep 2019 Tung T. Vu, Duy T. Ngo, Nguyen H. Tran, Hien Quoc Ngo, Minh N. Dao, Richard H. Middleton

This paper proposes a novel scheme for cell-free massive multiple-input multiple-output (CFmMIMO) networks to support any federated learning (FL) framework.

Signal Processing Information Theory Information Theory

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