Candidate Set

Candidate sets, collections of potential solutions or entities, are crucial in various machine learning tasks, impacting efficiency and accuracy. Current research focuses on optimizing candidate set selection and utilization, exploring methods to reduce their size without sacrificing performance (e.g., through pruning algorithms with certified error control) and developing alternative approaches that bypass the need for pre-defined sets altogether. This work is significant because efficient and effective candidate set management is vital for improving the speed and accuracy of applications ranging from information retrieval and entity linking to program synthesis and multi-objective optimization.