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: "Maximum set estimators with bounded estimation error"
  Abstract: We consider the linear regression problem of estimating a deterministic parameter vector x from observations y = Hx + w, where H is known, and w is additive noise. We seek an estimator whose estimation error does not exceed a given maximum error for as wide a range of conditions as possible. The maximum error is a design choice and is generally lower than the error provided by the well-known least-squares (LS) estimator. We develop estimators guaranteeing the required error for as large a parameter set as possible and for as large a noise level as possible. We discuss methods for finding these estimators and demonstrate that in many cases, the proposed estimators outperform the LS estimator.

Connected through hyperedge HE-1 (induced by source paper "Robust mean-squared error estimation in the presence of model uncertainties"):
  with members:
    (none)

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