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: "performance and construction of polar codes on symmetric binary input memoryless channels"
  Abstract: Channel polarization is a method of constructing capacity achieving codes for symmetric binary-input discrete memoryless channels (B-DMCs) [1]. In the original paper, the construction complexity is exponential in the blocklength. In this paper, a new construction method for arbitrary symmetric binary memoryless channel (B-MC) with linear complexity in the blocklength is proposed. Furthermore, new upper and lower bounds of the block error probability of polar codes are derived for the BEC and the arbitrary symmetric B-MC, respectively.

Connected through hyperedge HE-1 (induced by source paper "polar codes and their quantum domain counterparts"):
  with members:
    - "reinforcement learning for nested polar code construction"
    - "decoder tailored polar code design using the genetic algorithm"
    - "genetic algorithm based polar code construction for the awgn channel"
    - "improved bit flipping algorithm for successive cancellation decoding of polar codes"
    - "design of polar codes in 5g new radio"
    - "belief propagation decoding of polar codes on permuted factor graphs"
    - "improved successive cancellation flip decoding of polar codes based on error distribution"
    - "belief propagation list decoding of polar codes"

Connected through hyperedge HE-2 (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"
    - "polar codes robustness of the successive cancellation decoder with respect to quantization"
    - "how to construct polar codes"
    - "hardware architectures for successive cancellation decoding of polar codes"
    - "on the rate of channel polarization"

Connected through hyperedge HE-3 (induced by source paper "reinforcement learning for nested polar code construction"):
  with members:
    - "decoder in the loop genetic optimization based ldpc code design"
    - "decoder tailored polar code design using the genetic algorithm"
    - "ai coding learning to construct error correction codes"
    - "reinforcement learning from imperfect demonstrations"
    - "deepcode feedback codes via deep learning"
    - "pretraining deep actor critic reinforcement learning algorithms with expert demonstrations"
    - "scalable trust region method for deep reinforcement learning using kronecker factored approximation"
    - "proximal policy optimization algorithms"

Connected through hyperedge HE-4 (induced by source paper "ai coding learning to construct error correction codes"):
  with members:
    - "decoder tailored polar code design using the genetic algorithm"
    - "deepcode feedback codes via deep learning"
    - "parity check polar coding for 5g and beyond"
    - "an introduction to deep learning for the physical layer"
    - "beta expansion a theoretical framework for fast and recursive construction of polar codes"
    - "algebraic properties of polar codes from a new polynomial formalism"
    - "construction of polar codes with sublinear complexity"
    - "a rm polar codes"

Connected through hyperedge HE-5 (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"
    - "polar codes robustness of the successive cancellation decoder with respect to quantization"
    - "hardware architectures for successive cancellation decoding of polar codes"

Connected through hyperedge HE-6 (induced by source paper "a general construction and encoder implementation of polar codes"):
  with members:
    - "auto generation of pipelined hardware designs for polar encoder"
    - "low complexity puncturing and shortening of polar codes"
    - "rate compatible punctured polar codes optimal construction based on polar spectra"
    - "flexible and low complexity encoding and decoding of systematic polar codes"
    - "does gaussian approximation work well for the long length polar code construction"
    - "how to construct polar codes"
    - "a practical approach to polar codes"

Connected through hyperedge HE-7 (induced by source paper "study of non uniform channel polarization and design of polar codes with arbitrary rates"):
  with members:
    - "branch and bound precoding for multiuser mimo systems with 1 bit quantization"
    - "widely linear precoding for large scale mimo with iqi algorithms and performance analysis"
    - "low complexity puncturing and shortening of polar codes"
    - "a comparative study of polar code constructions for the awgn channel"
    - "adaptive reduced rank receive processing based on minimum symbol error rate criterion for large scale multiple antenna systems"
    - "how to construct polar codes"

Connected through hyperedge HE-8 (induced by source paper "weight distributions for successive cancellation decoding of polar codes"):
  with members:
    - "algebraic properties of polar codes from a new polynomial formalism"
    - "polar codes with dynamic frozen symbols and their decoding by directed search"
    - "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)