Tensor Network Structure Search

Tensor network structure search (TN-SS) focuses on efficiently finding optimal structures for representing high-dimensional data using tensor networks, a powerful tool in machine learning and computer vision. Current research emphasizes developing faster and more effective algorithms for TN-SS, including those inspired by singular value decomposition and employing meta-heuristic approaches like local enumeration and sampling within defined neighborhoods, as well as leveraging large language models to automate algorithm discovery. These advancements aim to overcome the computational challenges inherent in TN-SS, leading to more efficient and accurate models for various applications, such as language modeling and image processing.