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: "probabilistic analysis of linear programming decoding"
  Abstract: We initiate the probabilistic analysis of linear programming (LP) decoding of low-density parity-check (LDPC) codes. Specifically, we show that for a random LDPC code ensemble, the linear programming decoder of Feldman succeeds in correcting a constant fraction of errors with high probability. The fraction of correctable errors guaranteed by our analysis surpasses previous nonasymptotic results for LDPC codes, and in particular, exceeds the best previous finite-length result on LP decoding by a factor greater than ten. This improvement stems in part from our analysis of probabilistic bit-flipping channels, as opposed to adversarial channels. At the core of our analysis is a novel combinatorial characterization of LP decoding success, based on the notion of a flow on the Tanner graph of the code. An interesting by-product of our analysis is to establish the existence of ldquoprobabilistic expansionrdquo in random bipartite graphs, in which one requires only that almost every (as opposed to every) set of a certain size expands, for sets much larger than in the classical worst case setting.

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"
    - "linear programming decoding of spatially coupled 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"

Connected through hyperedge HE-2 (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"
    - "linear programming decoding of spatially coupled 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"

Connected through hyperedge HE-3 (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"
    - "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-4 (induced by source paper "lp sdp hierarchy lower bounds for decoding random ldpc codes"):
  with members:
    - "linear programming decoding of spatially coupled codes"
    - "spatially coupled ensembles universally achieve capacity under belief propagation"
    - "a new multilayered pcp and the hardness of hypergraph vertex cover"

Connected through hyperedge HE-5 (induced by source paper "linear programming decoding of spatially coupled codes"):
  with members:
    - "spatially coupled ensembles universally achieve capacity under belief propagation"
    - "information theoretically optimal compressed sensing via spatial coupling and approximate message passing"
    - "threshold saturation via spatial coupling why convolutional ldpc ensembles perform so well over the bec"
    - "scaling behavior of convolutional ldpc ensembles over the bec"
    - "towards low complexity 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 "sho fa robust compressive sensing with order optimal complexity measurements and bits"):
  with members:
    - "a family of optimal locally recoverable codes"
    - "biff bloom filter codes fast error correction for large data sets"
    - "fast matrix rank algorithms and applications"
    - "information theoretically optimal compressed sensing via spatial coupling and approximate message passing"
    - "one bit compressed sensing by linear programming"
    - "optimal phase transitions in compressed sensing"
    - "robust 1 bit compressive sensing via binary stable embeddings of sparse vectors"
    - "1 eps approximate sparse recovery"

Connected through hyperedge HE-7 (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-8 (induced by source paper "decomposition methods for large scale lp decoding"):
  with members:
    - "hierarchical and high girth qc ldpc codes"
    - "counting in graph covers a combinatorial characterization of the bethe entropy function"
    - "online alternating direction method"
    - "error floor approximation for ldpc codes in the awgn channel"
    - "improved linear programming decoding of ldpc codes and bounds on the minimum and fractional distance"
    - "l1 projections with box constraints"
    - "efficient implementation of linear programming decoding"
    - "interior point algorithms for linear programming decoding"

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)