[Deep Dive] Learning Decentralized Wireless Resource Allocations with Graph Neural Networks

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Deep Dive into Networked AI

NetAIStudio

10 episodes

2 days ago

Explore the cutting-edge of artificial intelligence (AI), machine learning, optimization, signal processing, wireless communications, networking, and broader networked systems. Join us as we dive deep into frontier research papers, uncover groundbreaking innovations, and discuss the possibilities shaping the future of technology and science.

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[Deep Dive] Learning Decentralized Wireless Resource Allocations with Graph Neural Networks

Deep Dive into Networked AI

18 minutes 44 seconds

9 months ago

[Deep Dive] Learning Decentralized Wireless Resource Allocations with Graph Neural Networks

In this episode, we dive into the combination of graph neural networks and unsupervised primal-dual learning, a model-free approach to scalable, intelligent wireless resource allocations. This episode is based on two papers published in IEEE Transactions on Signal Processing by Zhiyang Wang, Mark Eisen, and Alejandro Ribeiro.

Generated using NotebookLM from Google, this podcast highlights the key findings and implications of this research.

🎧 Read the papers here: [Eisen 2019], [Wang 2022]

📷 Cover Image Source: imagine.art, Microsoft Designer

🎵 BGM: Artlist.io

🛠️ Credits: NotebookLM by Google