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: "hardware decoders for polar codes an overview"
  Abstract: Polar codes are an exciting new class of error correcting codes that achieve the symmetric capacity of memoryless channels. Many decoding algorithms were developed and implemented, addressing various application requirements: from error-correction performance rivaling that of LDPC codes to very high throughput or low-complexity decoders. In this work, we review the state of the art in polar decoders implementing the successive-cancellation, belief propagation, and list decoding algorithms, illustrating their advantages.

Connected through hyperedge HE-1 (induced by source paper "decoder tailored polar code design using the genetic algorithm"):
  with members:
    - "genetic algorithm based polar code construction for the awgn channel"
    - "design of polar codes in 5g new radio"
    - "belief propagation list decoding of polar codes"
    - "mitigating clipping effects on error floors under belief propagation decoding of polar codes"
    - "polar code construction for list decoding"
    - "comparison of polar decoders with existing low density parity check and turbo decoders"
    - "minimum distance based construction of multi kernel polar codes"
    - "improving belief propagation decoding of polar codes using scattered exit charts"

Connected through hyperedge HE-2 (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"
    - "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"
    - "performance and construction of polar codes on symmetric binary input memoryless channels"

Connected through hyperedge HE-3 (induced by source paper "comparison of polar decoders with existing low density parity check and turbo decoders"):
  with members:
    - "fast low complexity decoders for low rate polar codes"
    - "llr based successive cancellation list decoder for polar codes with multibit decision"
    - "partitioned successive cancellation list decoding of polar codes"
    - "multi mode unrolled architectures for polar decoders"
    - "a high throughput list decoder architecture for polar codes"
    - "fast list decoders for polar codes"
    - "symbol decision successive cancellation list decoder for polar codes"
    - "tc throughput centric successive cancellation decoder hardware implementation for polar codes"

Connected through hyperedge HE-4 (induced by source paper "scaling deep learning based decoding of polar codes via partitioning"):
  with members:
    - "partitioned successive cancellation list decoding of polar codes"
    - "learning to decode linear codes using deep learning"
    - "combining belief propagation and successive cancellation list decoding of polar codes on a gpu platform"
    - "code design for short blocks a survey"
    - "fast list decoders for polar codes"
    - "theano a python framework for fast computation of mathematical expressions"
    - "tensorflow large scale machine learning on heterogeneous distributed systems"
    - "xj bp express journey belief propagation decoding for polar codes"

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)