1 citations · 1 across the 3 of their papers we have counts for
4 papers
Transformer Architecture with Minimal Inference Latency for Multi-Modal Wireless Networks
Minsu Kim, Walid Saad, Kui Wang +3
Next-generation wireless networks are expected to leverage multi-modal data sources to execute various wireless communication tasks such as beamforming and blockage prediction with…
Efficient Domain Generalization in Wireless Networks with Scarce Multi-Modal Data
Minsu Kim, Walid Saad, Doru Calin
In 6G wireless networks, multi-modal ML models can be leveraged to enable situation-aware network decisions in dynamic environments. However, trained ML models often fail to genera…
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…
Analysis of the Memorization and Generalization Capabilities of AI Agents: Are Continual Learners Robust?
Minsu Kim, Walid Saad
In continual learning (CL), an AI agent (e.g., autonomous vehicles or robotics) learns from non-stationary data streams under dynamic environments. For the practical deployment of…