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cs.LG2026
FedMTFI: Feature Importance Based Optimized Multi Teacher Knowledge Distillation in Heterogeneous Federated Learning Environment
Nazmus Shakib Shadin, Aaron Cummings, Xinyue Zhang +1
Federated learning (FL) is a decentralized approach that enables collaborative model training without exposing raw data. Instead of transferring sensitive data, it allows devices t…
cs.LG2025
Activation Sparsity Opportunities for Compressing General Large Language Models
Nobel Dhar, Bobin Deng, Md Romyull Islam +3
Deploying local AI models, such as Large Language Models (LLMs), to edge devices can substantially enhance devices' independent capabilities, alleviate the server's burden, and low…
cs.LG2024
The Robustness of Spiking Neural Networks in Communication and its Application towards Network Efficiency in Federated Learning
Manh V. Nguyen, Liang Zhao, Bobin Deng +3
Spiking Neural Networks (SNNs) have recently gained significant interest in on-chip learning in embedded devices and emerged as an energy-efficient alternative to conventional Arti…