activity
20162026
most citedSpaFL: Communication-Efficient Federated Learning with Sparse Models and Low computational Overhead

1 citations · 1 across the 7 of their papers we have counts for

collaborators

7 papers

cs.LG2026

A VAE-Driven Multi-Task Satellite-Aided Semantic Communication Framework for 6G-Enabled Connected Autonomous Vehicles

S. M. Abtahiul Alam, Niloy Das, Apurba Adhikary +3

The development of smart transportation systems and the introduction of 6G wireless communication technologies have significantly changed vehicle network topologies. Future connect…

cs.CV2026

FedDAP: Domain-Aware Prototype Learning for Federated Learning under Domain Shift

Huy Q. Le, Loc X. Nguyen, Yu Qiao +3

Federated Learning (FL) enables decentralized model training across multiple clients without exposing private data, making it ideal for privacy-sensitive applications. However, in…

eess.SY2025

Strategic Decision-Making Under Uncertainty through Bi-Level Game Theory and Distributionally Robust Optimization

Jiachen Shen, Jian Shi, Lei Fan +4

In strategic scenarios where decision-makers operate at different hierarchical levels, traditional optimization methods are often inadequate for handling uncertainties from incompl…

cs.CV2025

High-Frequency First: A Two-Stage Approach for Improving Image INR

Sumit Kumar Dam, Mrityunjoy Gain, Eui-Nam Huh +1

Implicit Neural Representations (INRs) have emerged as a powerful alternative to traditional pixel-based formats by modeling images as continuous functions over spatial coordinates…

cs.NI2025

DD-JSCC: Dynamic Deep Joint Source-Channel Coding for Semantic Communications

Avi Deb Raha, Apurba Adhikary, Mrityunjoy Gain +3

Deep Joint Source-Channel Coding (Deep-JSCC) has emerged as a promising semantic communication approach for wireless image transmission by jointly optimizing source and channel cod…

cs.LG2024★ 1 cited

SpaFL: Communication-Efficient Federated Learning with Sparse Models and Low computational Overhead

Minsu Kim, Walid Saad, Merouane Debbah +1

The large communication and computation overhead of federated learning (FL) is one of the main challenges facing its practical deployment over resource-constrained clients and syst…

cs.NI2016

Dynamic Clustering and User Association in Wireless Small Cell Networks with Social Considerations

Muhammad Ikram Ashraf, Mehdi Bennis, Walid Saad +2

In this paper, a novel social network-aware user association in wireless small cell networks with underlaid device-to-device (D2D) communication is investigated. The proposed appro…