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: "correcting a fraction of errors in nonbinary expander codes with linear programming"
  Abstract: A linear-programming decoder for nonbinary expander codes is presented. It is shown that the proposed decoder has the nearest-neighbor certificate properties. It is also shown that this decoder corrects any pattern of errors of a relative weight up to approximately 1/4δAδB (where δA and δB are the relative minimum distances of the constituent codes).

Connected through hyperedge HE-1 (induced by source paper "local optimality guarantees for optimal decoding based on paths"):
  with members:
    - "on decoding irregular tanner codes with local optimality guarantees"
    - "lp decoding of regular ldpc codes in memoryless channels"
    - "error bounds for repeat accumulate codes decoded via linear programming"
    - "probabilistic analysis of linear programming decoding"
    - "on the block error probability of lp decoding of ldpc codes"
    - "graph cover decoding and finite length analysis of message passing iterative decoding of ldpc codes"

Connected through hyperedge HE-2 (induced by source paper "on decoding irregular tanner codes with local optimality guarantees"):
  with members:
    - "counting in graph covers a combinatorial characterization of the bethe entropy function"
    - "convergence of weighted min sum decoding via dynamic programming on trees"
    - "lp decoding of regular ldpc codes in memoryless channels"
    - "error bounds for repeat accumulate codes decoded via linear programming"
    - "probabilistic analysis of linear programming decoding"
    - "on the block error probability of lp decoding of ldpc codes"
    - "graph cover decoding and finite length analysis of message passing iterative decoding of ldpc 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)