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: "modern coding theory the statistical mechanics and computer science point of view"
  Abstract: These are the notes for a set of lectures delivered by the two authors at the Les Houches Summer School on `Complex Systems' in July 2006. They provide an introduction to the basic concepts in modern (probabilistic) coding theory, highlighting connections with statistical mechanics. We also stress common concepts with other disciplines dealing with similar problems that can be generically referred to as `large graphical models'. #R##N#While most of the lectures are devoted to the classical channel coding problem over simple memoryless channels, we present a discussion of more complex channel models. We conclude with an overview of the main open challenges in the field.

Connected through hyperedge HE-1 (induced by source paper "on universal properties of capacity approaching ldpc code ensembles"):
  with members:
    - "on the design of universal ldpc codes"
    - "accumulate repeat accumulate codes capacity achieving ensembles of systematic codes for the erasure channel with bounded complexity"
    - "channel coding the road to channel capacity"
    - "how to find good finite length codes from art towards science"
    - "the generalized area theorem and some of its consequences"
    - "capacity achieving codes with bounded graphical complexity on noisy channels"
    - "tight bounds for ldpc and ldgm codes under map decoding"
    - "capacity achieving ensembles for the binary erasure channel with bounded complexity"

Connected through hyperedge HE-2 (induced by source paper "the generalized random energy model and its application to the statistical physics of ensembles of hierarchical codes"):
  with members:
    - "error exponents of erasure list decoding revisited via moments of distance enumerators"
    - "a statistical mechanical interpretation of instantaneous codes"
    - "relations between random coding exponents and the statistical physics of random codes"
    - "tight bounds for ldpc and ldgm codes under map decoding"

Connected through hyperedge HE-3 (induced by source paper "relations between random coding exponents and the statistical physics of random codes"):
  with members:
    - "the generalized random energy model and its application to the statistical physics of ensembles of hierarchical codes"
    - "error exponents of optimum decoding for the interference channel"
    - "error exponents of erasure list decoding revisited via moments of distance enumerators"
    - "a statistical mechanical interpretation of instantaneous codes"
    - "capacity of complexity constrained noise free cdma"

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)