Recovery Guarantee

Recovery guarantees in various fields focus on reliably reconstructing original data or system states after corruption, failure, or attacks. Current research emphasizes developing robust algorithms and models, including those based on reinforcement learning, optimization techniques (like LASSO and ADMM), and neural networks (e.g., DeepONets, Graph Neural Networks), to achieve accurate and efficient recovery even under challenging conditions such as noisy data, adversarial attacks, or hardware malfunctions. These advancements have significant implications for diverse applications, from improving the reliability of robotic systems and federated learning to enhancing medical image analysis and enabling more resilient infrastructure.