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: "polar codes robustness of the successive cancellation decoder with respect to quantization"
  Abstract: Polar codes provably achieve the capacity of a wide array of channels under successive decoding. This assumes infinite precision arithmetic. Given the successive nature of the decoding algorithm, one might worry about the sensitivity of the performance to the precision of the computation. #R##N#We show that even very coarsely quantized decoding algorithms lead to excellent performance. More concretely, we show that under successive decoding with an alphabet of cardinality only three, the decoder still has a threshold and this threshold is a sizable fraction of capacity. More generally, we show that if we are willing to transmit at a rate $\delta$ below capacity, then we need only $c \log(1/\delta)$ bits of precision, where $c$ is a universal constant.

Connected through hyperedge HE-1 (induced by source paper "finite level quantization procedures for construction and decoding of polar codes"):
  with members:
    - "quantized polar code decoders analysis and design"
    - "efficient polar code construction for higher order modulation"
    - "llr based successive cancellation 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"
    - "performance and construction of polar codes on symmetric binary input memoryless channels"
    - "on the rate of channel polarization"

Connected through hyperedge HE-2 (induced by source paper "ternary quantized polar code decoders analysis and design"):
  with members:
    - "quantized polar code decoders analysis and design"
    - "polarbear a 28 nm fd soi asic for decoding of polar codes"
    - "hardware decoders for polar codes an overview"
    - "llr based successive cancellation list decoding of polar codes"
    - "list decoding of polar codes"
    - "hardware architectures for successive cancellation decoding of polar codes"
    - "performance and construction of polar codes on symmetric binary input memoryless channels"

Connected through hyperedge HE-3 (induced by source paper "faulty successive cancellation decoding of polar codes for the binary erasure channel"):
  with members:
    - "analysis and design of finite alphabet iterative decoders robust to faulty hardware"
    - "density evolution and functional threshold for the noisy min sum decoder"
    - "density evolution for min sum decoding of ldpc codes under unreliable message storage"
    - "on the correlation between polarized becs"
    - "hardware architectures for successive cancellation decoding of polar codes"
    - "channel polarization a method for constructing capacity achieving codes for symmetric binary input memoryless channels"
    - "performance of ldpc codes under faulty iterative decoding"

Connected through hyperedge HE-4 (induced by source paper "varentropy decreases under the polar transform"):
  with members:
    - "channel polarization a method for constructing capacity achieving codes for symmetric binary input memoryless channels"

Connected through hyperedge HE-5 (induced by source paper "how to achieve the capacity of asymmetric channels"):
  with members:
    - "on the scaling exponent of polar codes for binary input energy harvesting channels"
    - "threshold saturation for nonbinary sc ldpc codes on the binary erasure channel"
    - "construction of polar codes with sublinear complexity"
    - "polar codes for broadcast channels"
    - "a scaling law to predict the finite length performance of spatially coupled ldpc codes"
    - "unified scaling of polar codes error exponent scaling exponent moderate deviations and error floors"
    - "finite length scaling for polar codes"
    - "achieving marton s region for broadcast channels using polar codes"

Connected through hyperedge HE-6 (induced by source paper "enabling complexity performance trade offs for successive cancellation decoding of polar codes"):
  with members:
    - "density evolution for min sum decoding of ldpc codes under unreliable message storage"
    - "on the correlation between polarized becs"
    - "on the construction of polar codes"
    - "how to construct polar codes"
    - "the multiobjective multidimensional knapsack problem a survey and a new approach"
    - "hardware architectures for successive cancellation decoding of polar codes"
    - "channel polarization a method for constructing capacity achieving codes for symmetric binary input memoryless channels"
    - "performance of ldpc codes under faulty iterative decoding"

Connected through hyperedge HE-7 (induced by source paper "polar codes speed of polarization and polynomial gap to capacity"):
  with members:
    - "finite length scaling for polar codes"
    - "improved bounds on the finite length scaling of polar codes"
    - "spatially coupled ensembles universally achieve capacity under belief propagation"
    - "universal bounds on the scaling behavior of polar codes"
    - "on the construction of polar codes"
    - "source and channel polarization over finite fields and reed solomon matrices"
    - "capacity achieving multiwrite wom codes"
    - "how to construct polar 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)