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 "a reduced complexity projection algorithm for admm based lp decoding"):
  Abstract: The Alternating Direction Method of Multipliers has recently been adapted for Linear Programming Decoding of Low-Density Parity-Check codes. The computation of the projection onto the parity polytope is the core of this algorithm and usually involves a sorting operation, which is the main effort of the projection. #R##N#In this paper, we present an algorithm with low complexity to compute this projection. The algorithm relies on new findings in the recursive structure of the parity polytope and iteratively fixes selected components. It requires up to 37% less arithmetical operations compared to state-of-the-art projections. Additionally, it does not involve a sorting operation, which is needed in all exact state-of-the-art projection algorithms. These two benefits make it appealing for efficient hard- and software implementations.

Includes members:
  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 "efficient qp admm decoder for binary ldpc codes and its performance analysis")
  Member "hardware based projection onto the parity polytope and probability simplex":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "efficient qp admm decoder for binary ldpc codes and its performance analysis")
  Member "adaptive cut generation algorithm for improved linear programming decoding of binary linear codes":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "admm based decoder for binary linear codes aided by deep learning")
  Member "decomposition methods for large scale lp decoding":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "admm based decoder for binary linear codes aided by deep learning")
  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")

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)