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: "spatial coupling as a proof technique"
  Abstract: The aim of this paper is to show that spatial coupling can be viewed not only as a means to build better graphical models, but also as a tool to better understand uncoupled models. The starting point is the observation that some asymptotic properties of graphical models are easier to prove in the case of spatial coupling. In such cases, one can then use the so-called interpolation method to transfer results known for the spatially coupled case to the uncoupled one. Our main application of this framework is to LDPC codes, where we use interpolation to show that the average entropy of the codeword conditioned on the observation is asymptotically the same for spatially coupled as for uncoupled ensembles. We use this fact to prove the so-called Maxwell conjecture for a large class of ensembles. In a first paper last year, we have successfully implemented this strategy for the case of LDPC ensembles where the variable node degree distribution is Poisson. In the current paper we now show how to treat the practically more relevant case of general variable degree distributions. In particular, regular ensembles fall within this framework. As we will see, a number of technical difficulties appear when compared to the simpler case of Pois son- distributed degrees. For our arguments to hold we need symmetry to be present. For coding, this symmetry follows from the channel symmetry; for general graphical models the required symmetry is called Nishimori symmetry.

Connected through hyperedge HE-1 (induced by source paper "concentration to zero bit error probability for regular ldpc codes on the binary symmetric channel proof by loop calculus"):
  with members:
    - "the bethe free energy allows to compute the conditional entropy of graphical code instances a proof from the polymer expansion"
    - "beyond the bethe free energy of ldpc codes via polymer expansions"
    - "decay of correlations for sparse graph error correcting codes"
    - "sharp bounds for optimal decoding of low density parity check codes"
    - "the generalized area theorem and some of its consequences"
    - "tight bounds for ldpc and ldgm codes under map decoding"

Connected through hyperedge HE-2 (induced by source paper "a simple proof of maxwell saturation for coupled scalar recursions"):
  with members:
    - "threshold saturation for spatially coupled ldpc and ldgm codes on bms channels"
    - "approaching the rate distortion limit with spatial coupling belief propagation and decimation"
    - "threshold saturation in spatially coupled constraint satisfaction problems"
    - "nonbinary spatially coupled ldpc codes on the binary erasure channel"
    - "a proof of threshold saturation for spatially coupled ldpc codes on bms channels"
    - "thresholds of spatially coupled systems via lyapunov s method"
    - "a simple proof of threshold saturation for coupled scalar recursions"
    - "spatially coupled ensembles universally achieve capacity under belief propagation"

Connected through hyperedge HE-3 (induced by source paper "threshold saturation for spatially coupled ldpc and ldgm codes on bms channels"):
  with members:
    - "approaching the rate distortion limit with spatial coupling belief propagation and decimation"
    - "threshold saturation in spatially coupled constraint satisfaction problems"
    - "a proof of threshold saturation for spatially coupled ldpc codes on bms channels"
    - "a simple proof of threshold saturation for coupled scalar recursions"
    - "spatially coupled ensembles universally achieve capacity under belief propagation"
    - "chains of mean field models"
    - "a phenomenological study on threshold improvement via spatial coupling"
    - "approaching capacity at high rates with iterative hard decision decoding"

Connected through hyperedge HE-4 (induced by source paper "error correcting codes and spatial coupling"):
  with members:
    - "finite length scaling for polar codes"
    - "a simple proof of threshold saturation for coupled scalar recursions"
    - "wave like solutions of general one dimensional spatially coupled systems"
    - "maxwell construction the hidden bridge between iterative and maximum a posteriori decoding"

Connected through hyperedge HE-5 (induced by source paper "approaching the rate distortion limit with spatial coupling belief propagation and decimation"):
  with members:
    - "threshold saturation for spatially coupled ldpc and ldgm codes on bms channels"
    - "threshold saturation in spatially coupled constraint satisfaction problems"
    - "a simple proof of threshold saturation for coupled scalar recursions"
    - "spatially coupled ensembles universally achieve capacity under belief propagation"
    - "lossy source coding via spatially coupled ldgm ensembles"
    - "chains of mean field models"
    - "fixed length lossy compression in the finite blocklength regime"
    - "information theoretically optimal compressed sensing via spatial coupling and approximate message passing"

Connected through hyperedge HE-6 (induced by source paper "on the convergence speed of spatially coupled ldpc ensembles"):
  with members:
    - "a proof of threshold saturation for spatially coupled ldpc codes on bms channels"
    - "a simple proof of threshold saturation for coupled scalar recursions"
    - "spatially coupled ensembles universally achieve capacity under belief propagation"
    - "wave like solutions of general one dimensional spatially coupled systems"
    - "threshold saturation via spatial coupling why convolutional ldpc ensembles perform so well over the bec"
    - "windowed decoding of spatially coupled codes"
    - "asymptotically regular ldpc codes with linear distance growth and thresholds close to capacity"
    - "terminated ldpc convolutional codes with thresholds close to capacity"

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)