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: "polarization as a novel architecture to boost the classical mismatched capacity of b dmcs"
  Abstract: We show that the mismatched capacity of binary discrete memoryless channels can be improved by channel combining and splitting via Ar{\i}kan's polar transformations. We also show that the improvement is possible even if the transformed channels are decoded with a mismatched polar decoder.

Connected through hyperedge HE-1 (induced by source paper "channel capacity of polar coding with a given polar mismatched successive cancellation decoder"):
  with members:
    - "a simple proof of fast polarization"
    - "on the scaling exponent of polar codes for binary input energy harvesting channels"
    - "a split reduced successive cancellation list decoder for polar codes"
    - "a low latency list successive cancellation decoding implementation for polar codes"
    - "a high throughput list decoder architecture for polar codes"
    - "fast list decoders for polar codes"
    - "symbol decision successive cancellation list decoder for polar codes"
    - "polar coding for processes with memory"

Connected through hyperedge HE-2 (induced by source paper "mismatched multi letter successive decoding for the multiple access channel"):
  with members:
    - "random coding error exponents for the two user interference channel"
    - "re proving channel polarization theorems an extremality and robustness analysis"
    - "a technique for deriving one shot achievability results in network information theory"
    - "multiuser coding techniques for mismatched decoding"
    - "mismatched decoding error exponents second order rates and saddlepoint approximations"
    - "a general formula for the mismatch capacity"
    - "on achievable rates for channels with mismatched decoding"
    - "multiuser random coding techniques for mismatched decoding"

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)