activity
20112024
most citedCooperative Multi-Bitrate Video Caching and Transcoding in Multicarrier NOMA-Assisted Heterogeneous Virtualized MEC Networks

25 citations · 69 across the 23 of their papers we have counts for

collaborators

26 papers

cs.NI2024

Leader Selection and Follower Association for UE-centric Distributed Learning in Future Wireless Networks

Saeedeh Parsaeefard, Sabine Roessel, Anousheh Gholami Ghavamabad +2

User equipment (UE) devices with high compute performance acting on data with dynamic and stochastic nature to train Artificial Intelligence/Machine Learning (AI/ML) models call fo…

eess.SP2022★ 11 cited

A Deep Learning-Based Approach for Cell Outage Compensation in NOMA Networks

Elaheh Vaezpour, Layla Majzoobi, Mohammad Akbari +2

Cell outage compensation enables a network to react to a catastrophic cell failure quickly and serve users in the outage zone uninterruptedly. Utilizing the promising benefits of n…

cs.NI2021

Interaction and Conflict Management in AI-assisted Operational Control Loops in 6G

Saeedeh Parsaeefard, Pooyan Habibi, Alberto Leon Garcia

This paper studies autonomous and AI-assisted control loops (ACLs) in the next generation of wireless networks in the lens of multi-agent environments. We will study the diverse in…

cs.LG2021★ 5 cited

Missing Data Estimation in Temporal Multilayer Position-aware Graph Neural Network (TMP-GNN)

Bahareh Najafi, Saeedeh Parsaeefard, Alberto Leon-Garcia

GNNs have been proven to perform highly effective in various node-level, edge-level, and graph-level prediction tasks in several domains. Existing approaches mainly focus on static…

cs.NI2021★ 6 cited

Toward Efficient Transfer Learning in 6G

Saeedeh Parsaeefard, Alberto Leon-Garcia

6G networks will greatly expand the support for data-oriented, autonomous applications for over the top (OTT) and networking use cases. The success of these use cases will depend o…

cs.NI2021

Generalized ADMM in Distributed Learning via Variational Inequality

Saeedeh Parsaeefard, Alberto Leon Garcia

Due to the explosion in size and complexity of modern data sets and privacy concerns of data holders, it is increasingly important to be able to solve machine learning problems in…