Algorithm Representation

Algorithm representation focuses on developing effective methods to encode algorithms' characteristics for tasks like automated algorithm selection and performance prediction. Current research emphasizes learning-based approaches, including the use of large language models to extract rich representations from algorithm code, and graph-based methods to capture algorithm structure and relationships. These advancements aim to improve automated machine learning workflows and optimize algorithm design by enabling more efficient selection of appropriate algorithms for specific problems, ultimately enhancing the performance and efficiency of various computational tasks.