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: "graph cover decoding and finite length analysis of message passing iterative decoding of ldpc codes"
  Abstract: The goal of the present paper is the derivation of a framework for the finite-length analysis of message-passing iterative decoding of low-density parity-check codes. To this end we introduce the concept of graph-cover decoding. Whereas in maximum-likelihood decoding all codewords in a code are competing to be the best explanation of the received vector, under graph-cover decoding all codewords in all finite covers of a Tanner graph representation of the code are competing to be the best explanation. We are interested in graph-cover decoding because it is a theoretical tool that can be used to show connections between linear programming decoding and message-passing iterative decoding. Namely, on the one hand it turns out that graph-cover decoding is essentially equivalent to linear programming decoding. On the other hand, because iterative, locally operating decoding algorithms like message-passing iterative decoding cannot distinguish the underlying Tanner graph from any covering graph, graph-cover decoding can serve as a model to explain the behavior of message-passing iterative decoding. Understanding the behavior of graph-cover decoding is tantamount to understanding the so-called fundamental polytope. Therefore, we give some characterizations of this polytope and explain its relation to earlier concepts that were introduced to understand the behavior of message-passing iterative decoding for finite-length codes.

Connected through hyperedge HE-1 (induced by source paper "efficient qp admm decoder for binary ldpc codes and its performance analysis"):
  with members:
    - "minimum polytope based linear programming decoder for ldpc codes via admm approach"
    - "the admm penalized decoder for ldpc codes"
    - "hardware based linear program decoding with the alternating direction method of multipliers"
    - "hardware based projection onto the parity polytope and probability simplex"
    - "mathematical programming decoding of binary linear codes theory and algorithms"
    - "adaptive cut generation algorithm for improved linear programming decoding of binary linear codes"
    - "improved linear programming decoding of ldpc codes and bounds on the minimum and fractional distance"
    - "efficient linear programming decoding of hdpc codes"

Connected through hyperedge HE-2 (induced by source paper "free pseudodistance growth rates for spatially coupled ldpc codes over the bec"):
  with members:
    - "spatially coupled ldpc codes constructed from protographs"
    - "spatially coupled ensembles universally achieve capacity under belief propagation"
    - "exact free distance and trapping set growth rates for ldpc convolutional codes"
    - "pseudocodewords of tanner graphs"

Connected through hyperedge HE-3 (induced by source paper "distance properties of short ldpc codes and their impact on the bp ml and near ml decoding performance"):
  with members:
    - "ml and near ml decoding of ldpc codes over the bec bounds and decoding algorithms"
    - "refined upper bounds on stopping redundancy of binary linear codes"
    - "on the pseudocodeword redundancy of binary linear codes"
    - "tree structure expectation propagation for decoding ldpc codes over binary erasure channels"
    - "permutation decoding and the stopping redundancy hierarchy of cyclic and extended cyclic codes"
    - "on the stopping distance and the stopping redundancy of codes"

Connected through hyperedge HE-4 (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-5 (induced by source paper "on the total power capacity of regular ldpc codes with iterative message passing decoders"):
  with members:
    - "on the energy complexity of ldpc decoder circuits"
    - "energy consumption of vlsi decoders"
    - "towards a communication theoretic understanding of system level power consumption"
    - "channel polarization a method for constructing capacity achieving codes for symmetric binary input memoryless channels"
    - "two bit message passing decoders for ldpc codes over the binary symmetric channel"

Connected through hyperedge HE-6 (induced by source paper "introduction to mathematical programming based error correction decoding"):
  with members:
    - "efficient maximum likelihood decoding of linear block codes on binary memoryless channels"
    - "towards combinatorial lp turbo decoding"
    - "mathematical programming decoding of binary linear codes theory and algorithms"
    - "adaptive cut generation algorithm for improved linear programming decoding of binary linear codes"
    - "polytope of correct linear programming decoding and low weight pseudo codewords"
    - "efficient implementation of linear programming decoding"
    - "a decomposition theory for binary linear codes"
    - "linear programming decoding of nonbinary linear codes"

Connected through hyperedge HE-7 (induced by source paper "towards approaching total power capacity transmit and decoding power minimization for ldpc codes"):
  with members:
    - "on the energy complexity of ldpc decoder circuits"
    - "energy consumption of vlsi decoders"
    - "towards a communication theoretic understanding of system level power consumption"
    - "channel polarization a method for constructing capacity achieving codes for symmetric binary input memoryless channels"
    - "two bit message passing decoders for ldpc codes over the binary symmetric channel"

Connected through hyperedge HE-8 (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"
    - "on the block error probability of lp 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)