Machine Learning for Wireless Communication and Networks

As wireless communication systems evolve to meet the demands of a hyper-connected world, artificial intelligence models are emerging as the driving force behind a new wave of technological innovation. This workshop will explore how state-of-the-art artificial intelligence and machine learning (ML) methods are poised to redefine the core of wireless networks providing solutions to old and new communication challenges. One of the central themes is semantic communication, where ML enables wireless networks to understand and transmit the meaning behind data, rather than the whole bitstream, drastically improving efficiency in bandwidth-constrained environments and presenting novel scenarios and possible applications that were not even conceivable a couple of years ago. Additionally, the rise of generative and language models for wireless communication is bringing new ways to compress and enhance signal transmissions, impacting several downstream applications such as autonomous driving, video streaming, and virtual reality. Concurrently with widening the range of applications, these models also bring novel challenges related to large models' computational demands or to the regenerated content's controllability and reliability.

Central to bridging ML and wireless communication is the study of inverse problems, where generative models play a pivotal role in reconstructing lost or incomplete signals, and solving ill-posed tasks inherent in communication systems constrained by noisy and interference channels with limited bandwidth. The workshop aims also to explore key areas such as multimodal content compression, post-training quantization, efficient semantic feature extraction, and designing trustworthy models tailored for resource-constrained and noisy environments, in which foundational ML research finds crucial applications in communication scenarios.

Paper submission deadline May 26th, 2025 Deadline Extended!!

Author notification June 9th, 2025

ML4Wireless Workshop July 18th, 2025

The submission link for ML4Wireless is https://openreview.net/group?id=ICML.cc/2025/Workshop/ML4Wireless. 

More detailed guidance can be found in the Call for Papers subpage of this site.