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: "on the block error probability of lp decoding of ldpc codes"
  Abstract: In his thesis, Wiberg showed the existence of thresholds for families of regular low-density parity-check codes under min-sum algorithm decoding. He also derived analytic bounds on these thresholds. In this paper, we formulate similar results for linear programming decoding of regular low-density parity-check codes.

Connected through hyperedge HE-1 (induced by source paper "impact of redundant checks on the lp decoding thresholds of ldpc codes"):
  with members:
    - "lp sdp hierarchy lower bounds for decoding random ldpc codes"
    - "linear programming decoding of spatially coupled codes"
    - "improved linear programming decoding of ldpc codes and bounds on the minimum and fractional distance"
    - "probabilistic analysis of linear programming decoding"
    - "a decomposition theory for binary linear codes"
    - "a cutting plane method based on redundant rows for improving fractional distance"
    - "adaptive methods for linear programming decoding"
    - "bounds on the threshold of linear programming decoding"

Connected through hyperedge HE-2 (induced by source paper "ldpc code density evolution in the error floor region"):
  with members:
    - "controlling the error floor in ldpc decoding"
    - "error floor approximation for ldpc codes in the awgn channel"
    - "on the dynamics of the error floor behavior in regular ldpc codes"
    - "the trapping redundancy of linear block codes"
    - "a general method for finding low error rates of ldpc codes"

Connected through hyperedge HE-3 (induced by source paper "ldpc codes for compressed sensing"):
  with members:
    - "counting in graph covers a combinatorial characterization of the bethe entropy function"
    - "compressed sensing how sharp is the restricted isometry property"
    - "compressed sensing performance bounds under poisson noise"
    - "construction of a large class of deterministic sensing matrices that satisfy a statistical isometry property"
    - "lp decoding meets lp decoding a connection between channel coding and compressed sensing"
    - "absdet pseudo codewords and perm pseudo codewords definitions and properties"
    - "necessary and sufficient conditions for sparsity pattern recovery"
    - "on the iterative decoding of high rate ldpc codes with applications in compressed sensing"

Connected through hyperedge HE-4 (induced by source paper "lp decoding of expander codes a simpler proof"):
  with members:
    - "lp decoding of regular ldpc codes in memoryless channels"
    - "efficient implementation of linear programming decoding"
    - "interior point algorithms for linear programming decoding"
    - "towards low complexity linear programming decoding"
    - "bounds on the threshold of linear programming decoding"
    - "some applications of coding theory in computational complexity"

Connected through hyperedge HE-5 (induced by source paper "local optimality guarantees for optimal decoding based on paths"):
  with members:
    - "correcting a fraction of errors in nonbinary expander codes with linear programming"
    - "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"
    - "graph cover decoding and finite length analysis of message passing iterative decoding of ldpc codes"

Connected through hyperedge HE-6 (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"
    - "correcting a fraction of errors in nonbinary expander codes with linear programming"
    - "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"
    - "graph cover decoding and finite length analysis of message passing iterative decoding of ldpc codes"

Connected through hyperedge HE-7 (induced by source paper "convergence of weighted min sum decoding via dynamic programming on trees"):
  with members:
    - "on the optimality of tree reweighted max product message passing"
    - "lp decoding of regular ldpc codes in memoryless channels"
    - "probabilistic analysis of linear programming decoding"
    - "sufficient conditions for convergence of the sum product algorithm"
    - "bounds on the threshold of linear programming decoding"

Connected through hyperedge HE-8 (induced by source paper "local optimality certificates for lp decoding of tanner codes"):
  with members:
    - "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"
    - "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)