Skip List

Skip lists are a probabilistic data structure designed for efficient searching, insertion, and deletion of elements, offering a balance between the simplicity of linked lists and the logarithmic search time of balanced trees. Current research focuses on enhancing skip list performance through techniques like integrating machine learning to optimize search times based on query frequency distributions, and adapting skip list principles to solve problems in other domains, such as dynamic optimal transport and efficient large language model inference. These advancements demonstrate the versatility of skip lists and their potential to improve the efficiency of algorithms across diverse applications, from data management to machine learning.