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: "Constructing deterministic finite-state automata in recurrent neural networks"
  Abstract: Recurrent neural networks that are  trained  to behave like deterministic finite-state automata (DFAs) can show deteriorating performance when tested on long strings. This deteriorating performance can be attributed to the instability of the internal representation of the learned DFA states. The use of a sigmoidel discriminant function together with the recurrent structure contribute to this instability. We prove that a simple algorithm can  construct  second-order recurrent neural networks with a sparse interconnection topology and sigmoidal discriminant function such that the internal DFA state representations are stable, that is, the constructed network correctly classifies strings of  arbitrary length . The algorithm is based on encoding strengths of weights directly into the neural network. We derive a relationship between the weight strength and the number of DFA states for robust string classification. For a DFA with  n  state and  m input alphabet symbols, the constructive algorithm generates a “programmed” neural network with  O ( n ) neurons and  O ( mn ) weights. We compare our algorithm to other methods proposed in the literature.

Connected through hyperedge HE-1 (induced by source paper "Stable encoding of large finite-state automata in recurrent neural networks with sigmoid discriminants"):
  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: Computer science