168 citations · 486 across the 27 of their papers we have counts for
5 papers · 1 filter
Energy-Efficient Massive MIMO for Federated Learning: Transmission Designs and Resource Allocations
Tung T. Vu, Hien Q. Ngo, Minh N. Dao +3
This work proposes novel synchronous, asynchronous, and session-based designs for energy-efficient massive multiple-input multiple-output networks to support federated learning (FL…
Energy-Efficient Massive MIMO for Serving Multiple Federated Learning Groups
Tung T. Vu, Hien Quoc Ngo, Duy T. Ngo +2
With its privacy preservation and communication efficiency, federated learning (FL) has emerged as a learning framework that suits beyond 5G and towards 6G systems. This work looks…
An adaptive splitting algorithm for the sum of three operators
Minh N. Dao, Hung M. Phan
Splitting algorithms for finding a zero of sum of operators often involve multiple steps which are referred to as forward or backward steps. Forward steps are the explicit use of t…
Generalized Bregman envelopes and proximity operators
Regina S. Burachik, Minh N. Dao, Scott B. Lindstrom
Every maximally monotone operator can be associated with a family of convex functions, called the Fitzpatrick family or family of representative functions. Surprisingly, in 2017, B…
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…