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: "improved successive cancellation decoding of polar codes"
  Abstract: As improved versions of the successive cancellation (SC) decoding algorithm, the successive cancellation list (SCL) decoding and the successive cancellation stack (SCS) decoding are used to improve the finite-length performance of polar codes. In this paper, unified descriptions of the SC, SCL, and SCS decoding algorithms are given as path search procedures on the code tree of polar codes. Combining the principles of SCL and SCS, a new decoding algorithm called the successive cancellation hybrid (SCH) is proposed. This proposed algorithm can provide a flexible configuration when the time and space complexities are limited. Furthermore, a pruning technique is also proposed to lower the complexity by reducing unnecessary path searching operations. Performance and complexity analysis based on simulations shows that under proper configurations, all the three improved successive cancellation (ISC) decoding algorithms can approach the performance of the maximum likelihood (ML) decoding but with acceptable complexity. With the help of the proposed pruning technique, the time and space complexities of ISC decoders can be significantly reduced and be made very close to those of the SC decoder in the high signal-to-noise ratio regime.

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 "sphere constraint based enumeration methods to analyze the minimum weight distribution of polar codes"):
  with members:
    - "does gaussian approximation work well for the long length polar code construction"
    - "low complexity sphere decoding of polar codes based on optimum path metric"
    - "list decoding of polar codes"
    - "an adaptive successive cancellation list decoder for polar codes with cyclic redundancy check"
    - "channel polarization a method for constructing capacity achieving codes for symmetric binary input memoryless channels"

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 "complexity adjustable sc decoding of polar codes for energy consumption reduction"):
  with members:
    - "relaxed polar codes"
    - "a split reduced successive cancellation list decoder for polar codes"
    - "fast list decoders for polar codes"
    - "llr based successive cancellation list decoding of polar codes"
    - "reduce the complexity of list decoding of polar codes by tree pruning"
    - "fast polar decoders algorithm and implementation"
    - "increasing the speed of polar list decoders"
    - "list decoding of polar codes"

Connected through hyperedge HE-5 (induced by source paper "learning to flip successive cancellation decoding of polar codes with lstm networks"):
  with members:
    - "improved successive cancellation flip decoding of polar codes based on error distribution"
    - "dynamic scflip decoding of polar codes"
    - "scaling deep learning based decoding of polar codes via partitioning"
    - "progressive bit flipping decoding of polar codes over layered critical sets"
    - "deep residual learning for image recognition"
    - "a low complexity improved successive cancellation decoder for polar codes"
    - "sequence to sequence learning with neural networks"
    - "list decoding of polar codes"

Connected through hyperedge HE-6 (induced by source paper "on the construction of g_n coset codes for parallel decoding"):
  with members:
    - "construction and decoding of product codes with non systematic polar codes"
    - "permutation decoding of polar codes"
    - "a new permutation decoding method for reed muller codes"
    - "a 5 16gbps decoder asic for polar code in 16nm finfet"
    - "a flip syndrome list polar decoder architecture for ultra low latency communications"
    - "strange attractor for efficient polar code design"
    - "reed muller codes achieve capacity on erasure channels"
    - "list decoding of polar codes"

Connected through hyperedge HE-7 (induced by source paper "polar codes analysis and construction based on polar spectrum"):
  with members:
    - "design of polar codes in 5g new radio"
    - "does gaussian approximation work well for the long length polar code construction"
    - "list decoding of polar codes"
    - "an adaptive successive cancellation list decoder for polar codes with cyclic redundancy check"
    - "how to construct polar codes"
    - "channel polarization a method for constructing capacity achieving codes for symmetric binary input memoryless channels"
    - "on the rate of channel polarization"

Connected through hyperedge HE-8 (induced by source paper "polar codes with memory"):
  with members:
    - "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"
    - "performance of polar codes for channel and source coding"

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)