human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "adaptive cut generation algorithm for improved linear programming decoding of binary linear codes"):
  Abstract: Linear programming (LP) decoding approximates maximum-likelihood (ML) decoding of a linear block code by relaxing the equivalent ML integer programming (IP) problem into a more easily solved LP problem. The LP problem is defined by a set of box constraints together with a set of linear inequalities called “parity inequalities” that are derived from the constraints represented by the rows of a parity-check matrix of the code and can be added iteratively and adaptively. In this paper, we first derive a new necessary condition and a new sufficient condition for a violated parity inequality constraint, or “cut,” at a point in the unit hypercube. Then, we propose a new and effective algorithm to generate parity inequalities derived from certain additional redundant parity check (RPC) constraints that can eliminate pseudocodewords produced by the LP decoder, often significantly improving the decoder error-rate performance. The cut-generating algorithm is based upon a specific transformation of an initial parity-check matrix of the linear block code. We also design two variations of the proposed decoder to make it more efficient when it is combined with the new cut-generating algorithm. Simulation results for several low-density parity-check (LDPC) codes demonstrate that the proposed decoding algorithms significantly narrow the performance gap between LP decoding and ML decoding.

Includes members:
  Member "mathematical programming decoding of binary linear codes theory and algorithms":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "efficient qp admm decoder for binary ldpc codes and its performance analysis")
  Member "efficient implementation of linear programming decoding":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "adaptive linear programming decoding of nonbinary linear codes over prime fields")
  Member "a cutting plane method based on redundant rows for improving fractional distance":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "impact of redundant checks on the lp decoding thresholds of ldpc codes")
  Member "a separation algorithm for improved lp decoding of linear block codes":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "efficient qp admm decoder for binary ldpc codes and its performance analysis")
  Member "pseudo codeword landscape":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "efficient qp admm decoder for binary ldpc codes and its performance analysis")
  Member "adaptive methods for linear programming decoding":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "efficient qp admm decoder for binary ldpc codes and its performance analysis")
  Member "graph cover decoding and finite length analysis of message passing iterative decoding of ldpc codes":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "efficient qp admm decoder for binary ldpc codes and its performance analysis")

Question: Please tell me which class the source paper 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)