Population Historical Information-Driven Evolutionary Multitask Neural Architecture Search

This research presents HIMT-NAS, an improved method for neural architecture search (NAS, the process of automatically designing neural network structures) that handles multiple tasks at once. The new approach tracks historical information about previous network designs across generations to reduce wasted search effort and adjusts how knowledge is shared between different tasks based on their similarity, addressing problems in existing multitask NAS methods.