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: "controlling the error floor in ldpc decoding"
  Abstract: The error floor of LDPC is revisited as an effect of dynamic message behavior in the so-called absorption sets of the code. It is shown that if the signal growth in the absorption sets is properly balanced by the growth of set-external messages, the error floor can be lowered to essentially arbitrarily low levels. Importance sampling techniques are discussed and used to verify the analysis, as well as to discuss the impact of iterations and message quantization on the code performance in the ultra-low BER (error floor) regime.

Connected through hyperedge HE-1 (induced by source paper "performance bounds and estimates for quantized ldpc decoders"):
  with members:
    - "thresholds of absorbing sets in low density parity check codes"
    - "on characterization of elementary trapping sets of variable regular ldpc codes"
    - "error floor approximation for ldpc codes in the awgn channel"
    - "quantized iterative message passing decoders with low error floor for ldpc codes"
    - "the trapping redundancy of linear block codes"

Connected through hyperedge HE-2 (induced by source paper "mitigating clipping effects on error floors under belief propagation decoding of polar codes"):
  with members:
    - "comparison of polar decoders with existing low density parity check and turbo decoders"
    - "on deep learning based channel decoding"
    - "improving belief propagation decoding of polar codes using scattered exit charts"
    - "combining belief propagation and successive cancellation list decoding of polar codes on a gpu platform"
    - "flexible length polar codes through graph based augmentation"
    - "reduced complexity belief propagation decoders for polar codes"
    - "unified scaling of polar codes error exponent scaling exponent moderate deviations and error floors"
    - "the effect of saturation on belief propagation decoding of ldpc codes"

Connected through hyperedge HE-3 (induced by source paper "decoding ldpc codes via noisy gradient descent bit flipping with re decoding"):
  with members:
    - "noisy gradient descent bit flip decoding for ldpc codes"
    - "gradient descent bit flipping algorithms for decoding ldpc codes"

Connected through hyperedge HE-4 (induced by source paper "analysis of saturated belief propagation decoding of low density parity check codes"):
  with members:
    - "spatially coupled ensembles universally achieve capacity under belief propagation"
    - "error floor approximation for ldpc codes in the awgn channel"
    - "quantized iterative message passing decoders with low error floor for ldpc codes"
    - "wave like solutions of general one dimensional spatially coupled systems"
    - "on the capacity of the discrete time channel with uniform output quantization"
    - "on the dynamics of the error floor behavior in regular ldpc codes"
    - "degree optimization and stability condition for the min sum decoder"

Connected through hyperedge HE-5 (induced by source paper "the effect of saturation on belief propagation decoding of ldpc codes"):
  with members:
    - "spatially coupled ensembles universally achieve capacity under belief propagation"
    - "error floor approximation for ldpc codes in the awgn channel"
    - "quantized iterative message passing decoders with low error floor for ldpc codes"
    - "on the capacity of the discrete time channel with uniform output quantization"
    - "on the dynamics of the error floor behavior in regular ldpc codes"
    - "degree optimization and stability condition for the min sum decoder"

Connected through hyperedge HE-6 (induced by source paper "ldpc code density evolution in the error floor region"):
  with members:
    - "error floor approximation for ldpc codes in the awgn channel"
    - "on the dynamics of the error floor behavior in regular ldpc codes"
    - "the trapping redundancy of linear block codes"
    - "on the block error probability of lp decoding of ldpc codes"
    - "a general method for finding low error rates of ldpc codes"

Connected through hyperedge HE-7 (induced by source paper "error floor approximation for ldpc codes in the awgn channel"):
  with members:
    - "ldpc code density evolution in the error floor region"
    - "the sum product algorithm for degree 2 check nodes and trapping sets"
    - "numerical issues affecting ldpc error floors"
    - "quantized iterative message passing decoders with low error floor for ldpc codes"
    - "on the dynamics of the error floor behavior in regular ldpc codes"
    - "the trapping redundancy of linear block codes"
    - "informed dynamic scheduling for belief propagation decoding of ldpc codes"
    - "a general method for finding low error rates of ldpc codes"

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)