human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge groups authors who co-authored the same paper.

Details of the hypergraph:
Center hyperedge (induced by source paper "A Decidable Dichotomy Theorem on Directed Graph Homomorphisms with Non-negative Weights"):
  Abstract: The complexity of graph homomorphism problems has been the subject of intense study. It is a long standing open problem to give a (decidable) complexity dichotomy theorem for the partition function of directed graph homomorphisms. In this paper, we prove a decidable complexity dichotomy theorem for this problem and our theorem applies to all non-negative weighted form of the problem: given any fixed matrix A with non-negative algebraic entries, the partition function Z_A(G) of directed graph homomorphisms from any directed graph G is either tractable in polynomial time or #P-hard, depending on the matrix A. The proof of the dichotomy theorem is combinatorial, but involves the definition of an infinite family of graph homomorphism problems. The proof of its decidability is algebraic using properties of polynomials.

Includes members:
  Member "The Computational Structure of Monotone Monadic SNP and Constraint Satisfaction: A Study through Datalog and Group Theory":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "A dichotomy theorem for constraint satisfaction problems on a 3-element set")
  Member "Taming the Curse of Dimensionality: Discrete Integration by Hashing and Optimization":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "Putting MRFs on a Tensor Train")
  Member "Improved FPTAS for Multi-spin Systems":
    also connected through other hyperedges:
      (none)

Question: Please tell me which research area the co-authored paper (i.e., the source paper of the center hyperedge) belongs to. The 4 classes are: Computer science, Mathematics, Engineering, Economics, Psychology, Business. Directly output the class name.

gpt: Mathematics