Jiannong Cao

Transmission-Efficient Federated Learning via Chessboard Convolutional Kernel

Reducing the communication cost to alleviate the contradiction between the limited bandwidth and huge transmitted parameters in Federated Learning (FL) is a persisting challenge. Since the transmission parameters obtained by vanilla convolution primarily rely on the product of kernel and channels, recent works (e.g., F...

ConfigTransLE: Large Language Models Enhanced Network Configuration Translation

Network device replacement, relocation, and vendor migration often require existing configurations to be translated to devices from different manufacturers while preserving network policies and operational behaviors. However, manual configuration translation is labor-intensive and requires substantial expertise, especi...

Diffusion-Guided Multi-Objective Reinforcement Learning for Hybrid Action Optimization in Collaborative Edge AIGC Networks

LYRA: Label-Free Structural Synchronization and Resource Allocation for UAV Edge Networks

A joint model update scheduling and resource allocation framework, aiming to maximize long-term semantic fidelity and resource efficiency of UAV edge intelligence systems, and a Lyapunov-guided discrete reinforcement learning algorithm that performs action space dimensionality reduction and transforms constraints into...