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 "efficient qp admm decoder for binary ldpc codes and its performance analysis"):
  Abstract: This paper presents an efficient quadratic programming (QP) decoder via the alternating direction method of multipliers (ADMM) technique, called QP-ADMM, for binary low-density parity-check (LDPC) codes. Its main contents are as follows: first, we relax maximum likelihood (ML) decoding problem to a non-convex quadratic program. Then, we develop an ADMM solving algorithm for the formulated non-convex QP decoding model. In the proposed QP-ADMM decoder, complex Euclidean projections onto the check polytope are eliminated and variables in each updated step can be solved analytically in parallel. Moreover, it is proved that the proposed ADMM algorithm converges to a stationary point of the non-convex QP problem under the assumption of sequence convergence. We also verify that the proposed decoder satisfies the favorable property of the all-zeros assumption. Furthermore, by exploiting the inside structures of the QP model, the complexity of the proposed algorithm in each iteration is shown to be linear in terms of LDPC code length. Simulation results demonstrate the effectiveness of the proposed QP-ADMM decoder.

Includes members:
  Member "minimum polytope based linear programming decoder for ldpc codes via admm approach":
    also connected through other hyperedges:
      (none)
  Member "the admm penalized decoder for ldpc codes":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "admm based decoder for binary linear codes aided by deep learning")
  Member "hardware based linear program decoding with the alternating direction method of multipliers":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a reduced complexity projection algorithm for admm based lp decoding")
  Member "hardware based projection onto the parity polytope and probability simplex":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a reduced complexity projection algorithm for admm based lp decoding")
  Member "mathematical programming decoding of binary linear codes theory and algorithms":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "adaptive linear programming decoding of nonbinary linear codes over prime fields")
  Member "adaptive cut generation algorithm for improved linear programming decoding of binary linear codes":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "admm based decoder for binary linear codes aided by deep learning")
  Member "improved linear programming decoding of ldpc codes and bounds on the minimum and fractional distance":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "the admm penalized decoder for ldpc codes")
  Member "efficient linear programming decoding of hdpc codes":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "deep learning methods for improved decoding of linear codes")

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)