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: "properties of the polarization transformations for the likelihood ratios of symmetric b dmcs"
  Abstract: In this paper we investigate, starting with a symmetric B-DMC, the evolution of various probabilities of the likelihood ratios of the synthetic channels created by the recursive application of the basic polarization transformations. The analysis provides a new perspective into the theory of channel polarization initiated by Ar{\i}kan and helps us to address a problem related to approximating the computations of the likelihood ratios of the synthetic channels.

Connected through hyperedge HE-1 (induced by source paper "re proving channel polarization theorems an extremality and robustness analysis"):
  with members:
    - "universal polar codes for more capable and less noisy channels and sources"
    - "the symmetric convex ordering a novel partial order for b dmcs ordering the information sets of polar codes"
    - "extremality for gallager s reliability function e_0"
    - "extremes of error exponents"
    - "list decoding of polar codes"
    - "on the construction of polar codes"
    - "how to construct polar codes"
    - "hardware architectures for successive cancellation decoding of polar codes"

Connected through hyperedge HE-2 (induced by source paper "a novel partial order for the information sets of polar codes over b dmcs"):
  with members:
    - "universal polar codes for more capable and less noisy channels and sources"
    - "extremality properties for the basic polarization transformations"
    - "on the construction of polar codes"
    - "how to construct polar codes"
    - "performance and construction of polar codes on symmetric binary input memoryless channels"
    - "channel polarization a method for constructing capacity achieving codes for symmetric binary input memoryless channels"

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)