IEEE Invites Papers on Autonomous Optimization in Networked AI for Signal Processing
The IEEE Signal Processing Society has announced a call for papers for a special issue of the IEEE Journal of Selected Topics in Signal Processing, focusing on Autonomous and Evolutive Optimization in Networked AI. This initiative aims to integrate traditional signal processing techniques with modern deep learning approaches, enabling systems to dynamically acquire high-quality data for continuous inferences in networked AI models. The concept emphasizes self-optimization through adaptive feedback mechanisms, allowing systems to optimize individual models by generating rewards and pseudo-labels online. The special issue will cover multiple disciplines, including signal processing, communications, and industrial automation, with applications in large language models, autonomous driving systems, and real-time 3D reconstruction. Submissions are open until June 15, 2026, with publication scheduled for January 2027. 
