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 "the approximate maximum likelihood certificate"):
  Abstract: A new property which relies on the linear programming (LP) decoder, the approximate maximum-likelihood certificate (AMLC), is introduced. When using the belief propagation decoder, this property is a measure of how close the decoded codeword is to the LP solution. Using upper bounding techniques, it is demonstrated that the conditional frame error probability given that the AMLC holds is, with some degree of confidence, below a threshold. In channels with low noise, this threshold is several orders of magnitude lower than the simulated frame error rate, and our bound holds with very high degree of confidence. In contrast, showing this error performance by simulation would require very long Monte Carlo runs. When the AMLC holds, our approach thus provides the decoder with extra error detection capability, which is especially important in applications requiring high data integrity.

Includes members:
  Member "improved linear programming decoding of ldpc codes and bounds on the minimum and fractional distance":
    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 "linear programming decoding of nonbinary linear codes":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "adaptive linear programming decoding of nonbinary linear codes over prime fields")
  Member "guessing facets polytope structure and improved lp decoder":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "belief propagation for linear programming")
  Member "adaptive methods for linear programming decoding":
    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 "on the asymptotic weight and stopping set distribution of regular ldpc ensembles":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "second order weight distributions")
  Member "towards low complexity linear programming decoding":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "adaptive linear programming decoding of nonbinary linear codes over prime fields")

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)