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: "linear programming decoding of spatially coupled codes"
  Abstract: For a given family of spatially coupled codes, we prove that the LP threshold on the BSC of the graph cover ensemble is the same as the LP threshold on the BSC of the derived spatially coupled ensemble. This result is in contrast with the fact that the BP threshold of the derived spatially coupled ensemble is believed to be larger than the BP threshold of the graph cover ensemble as noted by the work of Kudekar et al. (2011, 2012). To prove this, we establish some properties related to the dual witness for LP decoding which was introduced by Feldman et al. (2007) and simplified by Daskalakis et al. (2008). More precisely, we prove that the existence of a dual witness which was previously known to be sufficient for LP decoding success is also necessary and is equivalent to the existence of certain acyclic hyperflows. We also derive a sublinear (in the block length) upper bound on the weight of any edge in such hyperflows, both for regular LPDC codes and for spatially coupled codes and we prove that the bound is asymptotically tight for regular LDPC codes. Moreover, we show how to trade crossover probability for "LP excess" on all the variable nodes, for any binary linear code.

Connected through hyperedge HE-1 (induced by source paper "the admm penalized decoder for ldpc codes"):
  with members:
    - "hierarchical and high girth qc ldpc codes"
    - "an improved three weight message passing algorithm"
    - "counting in graph covers a combinatorial characterization of the bethe entropy function"
    - "mathematical programming decoding of binary linear codes theory and algorithms"
    - "error floor approximation for ldpc codes in the awgn channel"
    - "adaptive cut generation algorithm for improved linear programming decoding of binary linear codes"
    - "decomposition methods for large scale lp decoding"
    - "instantons causing iterative decoding to cycle"

Connected through hyperedge HE-2 (induced by source paper "lp decoding excess over symmetric channels"):
  with members:
    - "impact of redundant checks on the lp decoding thresholds of ldpc codes"

Connected through hyperedge HE-3 (induced by source paper "admm lp decoding of non binary ldpc codes in mathbb f _ 2 m"):
  with members:
    - "the admm penalized decoder for ldpc codes"
    - "low complexity lp decoding of nonbinary linear codes"
    - "online alternating direction method"
    - "adaptive cut generation algorithm for improved linear programming decoding of binary linear codes"
    - "decomposition methods for large scale lp decoding"
    - "lp decoding of regular ldpc codes in memoryless channels"
    - "efficient implementation of linear programming decoding"
    - "probabilistic analysis of linear programming decoding"

Connected through hyperedge HE-4 (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"
    - "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"
    - "on the block error probability of lp decoding of ldpc codes"
    - "bounds on the threshold of linear programming decoding"

Connected through hyperedge HE-5 (induced by source paper "lp sdp hierarchy lower bounds for decoding random ldpc codes"):
  with members:
    - "spatially coupled ensembles universally achieve capacity under belief propagation"
    - "probabilistic analysis of linear programming decoding"
    - "a new multilayered pcp and the hardness of hypergraph vertex cover"

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)