Noisy Communication

Noisy communication, encompassing imperfect information exchange in various communication systems, is a significant challenge across diverse fields, from machine learning to quantum computing. Current research focuses on developing robust algorithms and protocols that mitigate the negative effects of noise, including techniques like gradient tracking in federated learning, optimal transport theory for semantic communication, and rateless autoencoder codes for improved reliability and reduced decoding delay. These advancements aim to improve the reliability and efficiency of distributed systems and enhance the performance of machine learning models operating under real-world communication constraints.