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"
  Abstract: We consider the problem of efficiently constructing polar codes over binary memoryless symmetric (BMS) channels. The complexity of designing polar codes via an exact evaluation of the polarized channels to find which ones are "good" appears to be exponential in the block length. In \cite{TV11}, Tal and Vardy show that if instead the evaluation if performed approximately, the construction has only linear complexity. In this paper, we follow this approach and present a framework where the algorithms of \cite{TV11} and new related algorithms can be analyzed for complexity and accuracy. We provide numerical and analytical results on the efficiency of such algorithms, in particular we show that one can find all the "good" channels (except a vanishing fraction) with almost linear complexity in block-length (except a polylogarithmic factor).

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"
    - "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"
    - "performance and construction of polar codes on symmetric binary input memoryless channels"
    - "on the rate of channel polarization"

Connected through hyperedge HE-3 (induced by source paper "sublinear latency for simplified successive cancellation decoding of polar codes"):
  with members:
    - "log logarithmic time pruned polar coding"
    - "polar codes with exponentially small error at finite block length"
    - "polar code moderate deviation recovering the scaling exponent"
    - "partitioned list decoding of polar codes analysis and improvement of finite length performance"
    - "scaling exponent and moderate deviations asymptotics of polar codes for the awgn channel"
    - "fast and flexible successive cancellation list decoders for polar codes"
    - "binary linear codes with optimal scaling polar codes with large kernels"
    - "partitioned successive cancellation list decoding of polar codes"

Connected through hyperedge HE-4 (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-5 (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-6 (induced by source paper "from sequential decoding to channel polarization and back again"):
  with members:
    - "on the origin of polar coding"
    - "polar codes speed of polarization and polynomial gap to capacity"
    - "list decoding of polar codes"
    - "how to construct polar codes"
    - "on the rate of channel polarization"

Connected through hyperedge HE-7 (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"
    - "on the construction of polar codes for channels with moderate input alphabet sizes"
    - "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"

Connected through hyperedge HE-8 (induced by source paper "channel polarization through the lens of blackwell measures"):
  with members:
    - "general strong polarization"
    - "polar codes for broadcast channels"
    - "varentropy decreases under the polar transform"
    - "finite length scaling for polar codes"
    - "re proving channel polarization theorems an extremality and robustness analysis"
    - "polar codes speed of polarization and polynomial gap to capacity"
    - "polar codes for the two user multiple access channel"
    - "polar codes for q ary channels q 2 r"

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)