human: Given a node-centered hypergraph: <hypergraph>, where nodes represent authors and hyperedges represent groups of authors who co-authored the same paper.

Details of the hypergraph:
Center node: "Convex optimization based low-rank matrix decomposition for image restoration"
  Abstract: This paper addresses the problem of image denoising in the presence of significant corruption. Our method seeks an optimal set of image domain transformations such that the matrix of transformed images can be decomposed as the sum of a sparse matrix of errors and a low-rank matrix of recovered denoised images. We reduce this optimization problem to a sequence of convex programs minimizing the sum of the ? 1 - norm and the nuclear norm of the two component matrices, which can be solved efficiently using scalable convex optimization techniques. We verify the efficacy of the proposed image denoising algorithm through extensive experiments on both numerical simulations and different types of images, demonstrating its highly competent objective performance compared with several state-of-the-art methods for matrix decomposition and image denoising. Our subjective quality results compare favorably with those obtained by existing techniques, especially at high noise levels and with a large amount of missing data.

Connected through hyperedge HE-1 (induced by source paper "Image Deblurring and Super-Resolution by Adaptive Sparse Domain Selection and Adaptive Regularization"):
  with members:
    - "Image Denoising Via Sparse and Redundant Representations Over Learned Dictionaries"
    - "Image super-resolution reconstruction based on adaptive sparse representation: Image Super-resolution Reconstruction Based on Adaptive Sparse Representation"
    - "Image Super-resolution Reconstruction Utilizing the Combined Method of K-SVD and RAMP"
    - "Combining sparse representation and local rank constraint for single image super resolution"

Question: Please tell me which research area the center author belongs to. The 4 classes are: Computer science, Mathematics, Engineering, Economics, Psychology, Business. Directly output the class name.

gpt: Mathematics