human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "asymptotic improvement of the gilbert varshamov bound for linear codes"
  Abstract: The Gilbert-Varshamov (GV) bound states that the maximum size A2(n, d) of a binary code of length n and minimum distance d satisfies A2(n, d)ges2n/V(n, d-1) where V(n, d)=Sigmai=0 d(i n) stands for the volume of a Hamming ball of radius d. Recently, Jiang and Vardy showed that for binary nonlinear codes this bound can be improved to A2(n, d)gescn2n/(V(n, d-1)) for c a constant and d/nges0.499. In this paper, we show that certain asymptotic families of linear binary [n, n/2] random double circulant codes satisfy the same improved GV bound.

Connected through hyperedge HE-1 (induced by source paper "distribution of the minimal distance of random linear codes"):
  with members:
    - "on the weight distribution of random binary linear codes"

Connected through hyperedge HE-2 (induced by source paper "improved efficiency for explicit covering codes matching the sphere covering bound"):
  with members:
    - "chain generalization of covering code and deterministic algorithm for k sat"

Connected through hyperedge HE-3 (induced by source paper "probabilistic bounds on the trapping redundancy of linear codes"):
  with members:
    - "error floor approximation for ldpc codes in the awgn channel"
    - "the trapping redundancy of linear block codes"

Connected through hyperedge HE-4 (induced by source paper "cumulative distance enumerators of random codes and their thresholds"):
  with members:
    - "relations between random coding exponents and the statistical physics of random codes"

Question: Please tell me which class the center node belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.IT(Information Theory)