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20132026
most citedMulti-Stage Hybrid Federated Learning over Large-Scale D2D-Enabled Fog Networks

127 citations · 461 across the 65 of their papers we have counts for

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Showing 2024Show all

7 papers · 1 filter

cs.NI2024

Key Focus Areas and Enabling Technologies for 6G

Christopher G. Brinton, Mung Chiang, Kwang Taik Kim +14

We provide a taxonomy of a dozen enabling network architectures, protocols, and technologies that will define the evolution from 5G to 6G. These technologies span the network proto…

cs.LG2024

Unsupervised Federated Optimization at the Edge: D2D-Enabled Learning without Labels

Satyavrat Wagle, Seyyedali Hosseinalipour, Naji Khosravan +1

Federated learning (FL) is a popular solution for distributed machine learning (ML). While FL has traditionally been studied for supervised ML tasks, in many applications, it is im…

eess.SP2024

Minimum Description Feature Selection for Complexity Reduction in Machine Learning-based Wireless Positioning

Myeung Suk Oh, Anindya Bijoy Das, Taejoon Kim +2

Recently, deep learning approaches have provided solutions to difficult problems in wireless positioning (WP). Although these WP algorithms have attained excellent and consistent p…

eess.SY2024

Multi-Agent Hybrid SAC for Joint SS-DSA in CRNs

David R. Nickel, Anindya Bijoy Das, David J. Love +1

Opportunistic spectrum access has the potential to increase the efficiency of spectrum utilization in cognitive radio networks (CRNs). In CRNs, both spectrum sensing and resource a…

cs.LG2024

Smart Information Exchange for Unsupervised Federated Learning via Reinforcement Learning

Seohyun Lee, Anindya Bijoy Das, Satyavrat Wagle +1

One of the main challenges of decentralized machine learning paradigms such as Federated Learning (FL) is the presence of local non-i.i.d. datasets. Device-to-device transfers (D2D…

cs.LG2024

Complexity Reduction in Machine Learning-Based Wireless Positioning: Minimum Description Features

Myeung Suk Oh, Anindya Bijoy Das, Taejoon Kim +2

A recent line of research has been investigating deep learning approaches to wireless positioning (WP). Although these WP algorithms have demonstrated high accuracy and robust perf…

cs.IT2024

Coding for Gaussian Two-Way Channels: Linear and Learning-Based Approaches

Junghoon Kim, Taejoon Kim, Anindya Bijoy Das +3

Although user cooperation cannot improve the capacity of Gaussian two-way channels (GTWCs) with independent noises, it can improve communication reliability. In this work, we aim t…