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: "adaptive methods for linear programming decoding"
  Abstract: Detectability of failures of linear programming (LP) decoding and the potential for improvement by adding new constraints motivate the use of an adaptive approach in selecting the constraints for the underlying LP problem. In this paper, we make a first step in studying this method, and show that it can significantly reduce the complexity of the problem, which was originally exponential in the maximum check-node degree. We further show that adaptively adding new constraints, e.g. by combining parity checks, can provide large gains in the performance.

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 "a reduced complexity projection algorithm for admm based lp decoding"):
  with members:
    - "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"
    - "adaptive cut generation algorithm for improved linear programming decoding of binary linear codes"
    - "decomposition methods for large scale lp decoding"

Connected through hyperedge HE-3 (induced by source paper "minimum polytope based linear programming decoder for ldpc codes via admm approach"):
  with members:
    - "the admm penalized decoder for ldpc codes"
    - "decomposition methods for large scale lp decoding"

Connected through hyperedge HE-4 (induced by source paper "decoding reed muller codes using minimum weight parity checks"):
  with members:
    - "code design for short blocks a survey"
    - "performance comparison of short length error correcting codes"
    - "list decoding of polar codes"
    - "decomposition methods for large scale lp decoding"
    - "multiple bases belief propagation decoding of high density cyclic codes"
    - "iterative soft input soft output decoding of reed solomon codes by adapting the parity check matrix"

Connected through hyperedge HE-5 (induced by source paper "a branch price and cut algorithm for optimal decoding of ldpc codes"):
  with members:
    - "nash codes for noisy channels"
    - "adaptive cut generation algorithm for improved linear programming decoding of binary linear codes"
    - "decomposition methods for large scale lp decoding"
    - "budget optimal task allocation for reliable crowdsourcing systems"
    - "a separation algorithm for improved lp decoding of linear block codes"

Connected through hyperedge HE-6 (induced by source paper "adaptive linear programming decoding of nonbinary linear codes over prime fields"):
  with members:
    - "hardware based linear program decoding with the alternating direction method of multipliers"
    - "on the finite length scaling of ternary polar codes"
    - "low complexity lp decoding of nonbinary linear codes"
    - "mathematical programming decoding of binary linear codes theory and algorithms"
    - "adaptive cut generation algorithm for improved linear programming decoding of binary linear codes"
    - "decomposition methods for large scale lp decoding"
    - "efficient implementation of linear programming decoding"
    - "linear programming decoding of nonbinary linear codes"

Connected through hyperedge HE-7 (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-8 (induced by source paper "hardware based linear program decoding with the alternating direction method of multipliers"):
  with members:
    - "1 bit massive mu mimo precoding in vlsi"
    - "hardware based projection onto the parity polytope and probability simplex"
    - "lp decodable multipermutation codes"
    - "hierarchical and high girth qc ldpc codes"
    - "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"
    - "towards low complexity 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)