42 citations · 43 across the 16 of their papers we have counts for
9 papers · 1 filter
Optimal RIS Placement in Multi-User MISO Systems with User Randomness
Abhishek Rajasekaran, Mehdi Karbalayghareh, Xiaoyan Ma +2
It is well established that the performance of reconfigurable intelligent surface (RIS)-assisted systems critically depends on the optimal placement of the RIS. Previous works cons…
Coherence-Aware Distributed Learning under Heterogeneous Downlink Impairments
Mehdi Karbalayghareh, David J. Love, Christopher G. Brinton
The performance of federated learning (FL) over wireless networks critically depends on accurate and timely channel state information (CSI) across distributed devices. This require…
Federated Foundation Models in Harsh Wireless Environments: Prospects, Challenges, and Future Directions
Evan Chen, Seyyedali Hosseinalipour, Christopher G. Brinton +1
Foundation models (FMs) have shown remarkable capabilities in generalized intelligence, multimodal understanding, and adaptive learning across a wide range of domains. However, the…
Physics-based Generative Models for Geometrically Consistent and Interpretable Wireless Channel Synthesis
Satyavrat Wagle, Akshay Malhotra, Shahab Hamidi-Rad +3
In recent years, machine learning (ML) methods have become increasingly popular in wireless communication systems for several applications. A critical bottleneck for designing ML s…
Federated Learning for Cyber Physical Systems: A Comprehensive Survey
Minh K. Quan, Pubudu N. Pathirana, Mayuri Wijayasundara +5
The integration of machine learning (ML) in cyber physical systems (CPS) is a complex task due to the challenges that arise in terms of real-time decision making, safety, reliabili…
Multi-Agent Reinforcement Learning for Graph Discovery in D2D-Enabled Federated Learning
Satyavrat Wagle, Anindya Bijoy Das, David J. Love +1
Augmenting federated learning (FL) with device-to-device (D2D) communications can help improve convergence speed and reduce model bias through local information exchange. However,…
Learning-Based Two-Way Communications: Algorithmic Framework and Comparative Analysis
David R. Nickel, Anindya Bijoy Das, David J. Love +1
Machine learning (ML)-based feedback channel coding has garnered significant research interest in the past few years. However, there has been limited research exploring ML approach…
Physics-Informed Generative Approaches for Wireless Channel Modeling
Satyavrat Wagle, Akshay Malhotra, Shahab Hamidi-Rad +3
In recent years, machine learning (ML) methods have become increasingly popular in wireless communication systems for several applications. A critical bottleneck for designing ML s…
Cooperative Decentralized Backdoor Attacks on Vertical Federated Learning
Seohyun Lee, Wenzhi Fang, Anindya Bijoy Das +3
Federated learning (FL) is vulnerable to backdoor attacks, where adversaries alter model behavior on target classification labels by embedding triggers into data samples. While the…