IEEE

Federated Meta-Reinforcement Learning for Adaptive Wireless Networks: A Unified Framework Integrating Proximal Policy Optimization, Meta-Learning, and Graph Neural Networks

Abstract: Proposed Federated Meta-Reinforcement Learning (FMRL) integrates PPO, meta-learning, and graph neural networks (GNNs) into a privacy-preserving distributed framework for adaptive wireless ...
IEEE

HINSCAN: Efficient Structural Graph Clustering Over Heterogeneous Information Networks

Abstract: Structural graph clustering (SCAN) is one of the most popular graph clustering paradigms, and has attracted plenty of attention recently. Existing solutions assume that the input graphs is ...
InfoWorld

Reactive state management with JavaScript Signals

Learn how frameworks like Solid, Svelte, and Angular are using the Signals pattern to deliver reactive state without the ...