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 flip decoding of polar codes based on error distribution"
  Abstract: Polar codes are a class of linear block codes that provably achieves channel capacity, and have been selected as a coding scheme for 5th generation wireless communication standards. Successive-cancellation (SC) decoding of polar codes has mediocre error-correction performance on short to moderate codeword lengths: the SC-Flip decoding algorithm is one of the solutions that have been proposed to overcome this issue. On the other hand, SC-Flip has a higher implementation complexity compared to SC due to the required log-likelihood ratio (LLR) selection and sorting process. Moreover, it requires a high number of iterations to reach good error-correction performance. In this work, we propose two techniques to improve the SC-Flip decoding algorithm for low-rate codes, based on the observation of channel-induced error distributions. The first one is a fixed index selection (FIS) scheme to avoid the substantial implementation cost of LLR selection and sorting with no cost on error-correction performance. The second is an enhanced index selection (EIS) criterion to improve the error-correction performance of SC-Flip decoding. A reduction of 24.6% in the implementation cost of logic elements is estimated with the FIS approach, while simulation results show that EIS leads to an improvement on error-correction performance improvement up to 0.34 dB at a target FER of 10−4.

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"
    - "belief propagation list decoding of polar codes"
    - "dynamic scflip decoding of polar codes"

Connected through hyperedge HE-2 (induced by source paper "deep learning aided successive cancellation decoding of polar codes"):
  with members:
    - "neural dynamic successive cancellation flip decoding of polar codes"
    - "improved bit flipping algorithm for successive cancellation decoding of polar codes"
    - "neural belief propagation decoding of crc polar concatenated codes"
    - "partitioned successive cancellation flip decoding of polar codes"
    - "deep learning methods for improved decoding of linear codes"
    - "dynamic scflip decoding of polar codes"
    - "scaling deep learning based decoding of polar codes via partitioning"
    - "llr based successive cancellation list decoding of polar codes"

Connected through hyperedge HE-3 (induced by source paper "neural dynamic successive cancellation flip decoding of polar codes"):
  with members:
    - "improved bit flipping algorithm for successive cancellation decoding of polar codes"
    - "neural belief propagation decoding of crc polar concatenated codes"
    - "partitioned successive cancellation flip decoding of polar codes"
    - "deep learning methods for improved decoding of linear codes"
    - "dynamic scflip decoding of polar codes"
    - "neural offset min sum decoding"
    - "tensorflow a system for large scale machine learning"
    - "llr based successive cancellation list decoding of polar codes"

Connected through hyperedge HE-4 (induced by source paper "learning to flip successive cancellation decoding of polar codes with lstm networks"):
  with members:
    - "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"
    - "improved successive cancellation decoding of polar codes"
    - "list decoding of polar codes"

Connected through hyperedge HE-5 (induced by source paper "design of polar codes in 5g new radio"):
  with members:
    - "on list decoding of 5g nr polar codes"
    - "parity check polar coding for 5g and beyond"
    - "design and implementation of a polar codes blind detection scheme"
    - "circular buffer rate matched polar codes"
    - "partitioned list decoding of polar codes analysis and improvement of finite length performance"
    - "on the error probability of short concatenated polar and cyclic codes with interleaving"
    - "on puncturing strategies for polar codes"
    - "polar code construction for list decoding"

Connected through hyperedge HE-6 (induced by source paper "improved bit flipping algorithm for successive cancellation decoding of polar codes"):
  with members:
    - "partitioned successive cancellation flip decoding of polar codes"
    - "dynamic scflip decoding of polar codes"
    - "an improved scflip decoder for polar codes"
    - "partitioned list decoding of polar codes analysis and improvement of finite length performance"
    - "polarbear a 28 nm fd soi asic for decoding of polar codes"
    - "on error correction performance and implementation of polar code list decoders for 5g"
    - "fast and flexible successive cancellation list decoders for polar codes"
    - "progressive bit flipping decoding of polar codes over layered critical sets"

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)