Special Issue on the Fourth Workshop on Learning-augmented Algorithms: Theory and Applications (LATA 2026)

Learning-augmented algorithms, also known as algorithms with predictions or with AI/ML advice, are a rapidly growing area of research at the intersection of machine learning and the design and analysis of algorithms. We were pleased to host the fourth annual workshop on Learning-augmented Algorithms: Theory and Applications (LATA 2026) on June 12, 2026, co-located with ACM SIGMETRICS 2026 in Ann Arbor, Michigan. The program comprised three invited keynote talks and seven contributed talks, covering topics ranging from algorithm design and learning-theoretic guarantees for predictions to applications of learning-augmented algorithms to domains such as energy systems and large language model (LLM) systems.