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20222026
most citedGenerative AI-driven Semantic Communication Framework for NextG Wireless Network

6 citations · 20 across the 20 of their papers we have counts for

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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.LG2026

Domain-Aware Hybrid Quantum Learning via Correlation-Guided Circuit Design for Crime Pattern Analytics

Niloy Das, Apurba Adhikary, Sheikh Salman Hassan +4

Crime pattern analysis is critical for law enforcement and predictive policing, yet the surge in criminal activities from rapid urbanization creates high-dimensional, imbalanced da…

cs.LG2026

A Multi-Prototype-Guided Federated Knowledge Distillation Approach in AI-RAN Enabled Multi-Access Edge Computing System

Luyao Zou, Hayoung Oh, Chu Myaet Thwal +3

With the development of wireless network, Multi-Access Edge Computing (MEC) and Artificial Intelligence (AI)-native Radio Access Network (RAN) have attracted significant attention.…

cs.LG2024★ 1 cited

Logit Calibration and Feature Contrast for Robust Federated Learning on Non-IID Data

Yu Qiao, Chaoning Zhang, Apurba Adhikary +1

Federated learning (FL) is a privacy-preserving distributed framework for collaborative model training on devices in edge networks. However, challenges arise due to vulnerability t…

cs.LG2023★ 1 cited

MP-FedCL: Multiprototype Federated Contrastive Learning for Edge Intelligence

Yu Qiao, Md. Shirajum Munir, Apurba Adhikary +4

Federated learning-assisted edge intelligence enables privacy protection in modern intelligent services. However, not independent and identically distributed (non-IID) distribution…

cs.LG2022★ 1 cited

Impact Learning: A Learning Method from Features Impact and Competition

Nusrat Jahan Prottasha, Saydul Akbar Murad, Abu Jafar Md Muzahid +5

Machine learning is the study of computer algorithms that can automatically improve based on data and experience. Machine learning algorithms build a model from sample data, called…