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: "on the construction of polar codes for channels with moderate input alphabet sizes"
  Abstract: Current deterministic algorithms for the construction of polar codes can only be argued to be practical for channels with small input alphabet sizes. In this paper, we show that any construction algorithm for channels with moderate input alphabet size which follows the paradigm of "degrading after each polarization step" will inherently be impractical with respect to a certain "hard" underlying channel. This result also sheds light on why the construction of LDPC codes using density evolution is impractical for channels with moderate sized input alphabets.

Connected through hyperedge HE-1 (induced by source paper "universal polarization for processes with memory"):
  with members:
    - "a simple proof of fast polarization"
    - "fast polarization for processes with memory"
    - "polar coding for processes with memory"
    - "construction of polar codes for arbitrary discrete memoryless channels"
    - "universal polar codes for more capable and less noisy channels and sources"
    - "joint successive cancellation decoding of polar codes over intersymbol interference channels"
    - "universal source polarization and an application to a multi user problem"
    - "channel upgradation for non binary input alphabets and macs"

Connected through hyperedge HE-2 (induced by source paper "information distilling quantizers"):
  with members:
    - "strong data processing inequalities for channels and bayesian networks"
    - "opening the black box of deep neural networks via information"
    - "greedy merge degrading has optimal power law"
    - "bounds on the entropy of a function of a random variable and their applications"
    - "justification of logarithmic loss via the benefit of side information"
    - "deep learning and the information bottleneck principle"
    - "on maximal correlation hypercontractivity and the data processing inequality studied by erkip and cover"
    - "on the construction of polar codes"

Connected through hyperedge HE-3 (induced by source paper "polarization weight family methods for polar code construction"):
  with members:
    - "beta expansion a theoretical framework for fast and recursive construction of polar codes"
    - "list decoding of polar codes"
    - "on the construction of polar codes"
    - "how to construct polar codes"

Connected through hyperedge HE-4 (induced by source paper "greedy merge degrading has optimal power law"):
  with members:
    - "information distilling quantizers"
    - "construction of polar codes for arbitrary discrete memoryless channels"
    - "channel upgradation for non binary input alphabets and macs"
    - "on the construction of polar codes"
    - "at low snr asymmetric quantizers are better"
    - "how to construct polar codes"
    - "achieving the secrecy capacity of wiretap channels using polar codes"
    - "quantization of binary input discrete memoryless channels"

Connected through hyperedge HE-5 (induced by source paper "equidistant polarizing transforms"):
  with members:
    - "construction of polar codes for arbitrary discrete memoryless channels"
    - "entropies of weighted sums and applications to polar codes"
    - "polar codes for q ary channels q 2 r"
    - "how to construct polar codes"
    - "channel polarization a method for constructing capacity achieving codes for symmetric binary input memoryless channels"
    - "polarization for arbitrary discrete memoryless channels"
    - "on the rate of channel polarization"

Connected through hyperedge HE-6 (induced by source paper "construction of polar codes for arbitrary discrete memoryless channels"):
  with members:
    - "a comparative study of polar code constructions for the awgn channel"
    - "ergodic theory meets polarization ii a foundation of polarization theory"
    - "practical polar code construction using generalised generator matrices"
    - "upgraded approximation of non binary alphabets for polar code construction"
    - "channel upgradation for non binary input alphabets and macs"
    - "on the construction and decoding of concatenated polar codes"
    - "universal polar codes"
    - "constructing polar codes using iterative bit channel upgrading"

Connected through hyperedge HE-7 (induced by source paper "does gaussian approximation work well for the long length polar code construction"):
  with members:
    - "improved successive cancellation decoding of polar codes"
    - "list decoding of polar codes"
    - "an adaptive successive cancellation list decoder for polar codes with cyclic redundancy check"
    - "on the construction of polar codes"
    - "how to construct polar codes"
    - "channel polarization a method for constructing capacity achieving codes for symmetric binary input memoryless channels"

Connected through hyperedge HE-8 (induced by source paper "evaluation and optimization of gaussian approximation for polar codes"):
  with members:
    - "a split reduced successive cancellation list decoder for polar codes"
    - "improved successive cancellation decoding of polar codes"
    - "list decoding of polar codes"
    - "how to construct polar codes"
    - "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)