Tensor Optimization

Tensor optimization focuses on efficiently solving optimization problems involving multi-dimensional data structures called tensors, aiming to improve computational speed and resource utilization. Current research emphasizes developing and applying tensor-based algorithms across diverse fields, including deep learning (e.g., optimizing neural network architectures and accelerating training), computer vision (e.g., kinship verification and facial expression recognition), and energy-efficient AI. These advancements are significant because they enable faster, more efficient, and more sustainable solutions for a wide range of applications, from large-scale scientific computing to resource-constrained mobile devices.