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: "channel polarization a method for constructing capacity achieving codes for symmetric binary input memoryless channels"
  Abstract: A method is proposed, called channel polarization, to construct code sequences that achieve the symmetric capacity I(W) of any given binary-input discrete memoryless channel (B-DMC) W. The symmetric capacity is the highest rate achievable subject to using the input letters of the channel with equal probability. Channel polarization refers to the fact that it is possible to synthesize, out of N independent copies of a given B-DMC W, a second set of N binary-input channels {WN(i)1 les i les N} such that, as N becomes large, the fraction of indices i for which I(WN(i)) is near 1 approaches I(W) and the fraction for which I(WN(i)) is near 0 approaches 1-I(W). The polarized channels {WN(i)} are well-conditioned for channel coding: one need only send data at rate 1 through those with capacity near 1 and at rate 0 through the remaining. Codes constructed on the basis of this idea are called polar codes. The paper proves that, given any B-DMC W with I(W) > 0 and any target rate R< I(W) there exists a sequence of polar codes {Cfrn;nges1} such that Cfrn has block-length N=2n , rate ges R, and probability of block error under successive cancellation decoding bounded as Pe(N,R) les O(N-1/4) independently of the code rate. This performance is achievable by encoders and decoders with complexity O(N logN) for each.

Connected through hyperedge HE-1 (induced by source paper "reed muller codes theory and algorithms"):
  with members:
    - "reed muller codes polarize"
    - "recursive projection aggregation decoding of reed muller codes"
    - "general strong polarization"
    - "on the performance of reed muller codes with respect to random errors and erasures"
    - "decoding reed muller codes using minimum weight parity checks"
    - "on the bias of reed muller codes over odd prime fields"
    - "almost optimal scaling of reed muller codes on bec and bsc channels"
    - "soft decision decoding of reed muller codes recursive lists"

Connected through hyperedge HE-2 (induced by source paper "explicit codes for the wiretap channel a unified design framework"):
  with members:
    - "a new wiretap channel model and its strong secrecy capacity"
    - "empirical and strong coordination via soft covering with polar codes"
    - "coding schemes for achieving strong secrecy at negligible cost"
    - "semantic security capacity for wiretap channels of type ii"
    - "achieving secrecy capacity of the wiretap channel and broadcast channel with a confidential component"
    - "polar coding for the broadcast channel with confidential messages a random binning analogy"
    - "how to achieve the capacity of asymmetric channels"
    - "an information theoretic approach to secret sharing"

Connected through hyperedge HE-3 (induced by source paper "polar decreasing monomial cartesian codes"):
  with members:
    - "monomial cartesian codes and their duals with applications to lcd codes quantum codes and locally recoverable codes"
    - "design of polar codes in 5g new radio"
    - "multi kernel polar codes proof of polarization and error exponents"
    - "algebraic properties of polar codes from a new polynomial formalism"
    - "fast list decoders for polar codes"
    - "multi kernel construction of polar codes"
    - "on the second hamming weight of some reed muller type codes"
    - "list decoding of polar codes"

Connected through hyperedge HE-4 (induced by source paper "crc aided belief propagation list decoding of polar codes"):
  with members:
    - "partially permuted multi trellis belief propagation for polar codes"
    - "on the decoding of polar codes on permuted factor graphs"
    - "neural belief propagation decoding of crc polar concatenated codes"
    - "belief propagation decoding of polar codes on permuted factor graphs"
    - "belief propagation list decoding of polar codes"
    - "decoding reed muller and polar codes by successive factor graph permutations"
    - "mitigating clipping effects on error floors under belief propagation decoding of polar codes"
    - "combining belief propagation and successive cancellation list decoding of polar codes on a gpu platform"

Connected through hyperedge HE-5 (induced by source paper "a geometric view of the service rates of codes problem and its application to the service rate of the first order reed muller codes"):
  with members:
    - "load balancing performance in distributed storage with regular balanced redundancy"
    - "service rate region of content access from erasure coded storage"
    - "simplex queues for hot data download"
    - "on distributed storage allocations of large files for maximum service rate"
    - "on the service capacity region of accessing erasure coded content"
    - "on storage allocation for maximum service rate in distributed storage systems"
    - "many to many matching games for proactive social caching in wireless small cell networks"
    - "distributed storage allocations"

Connected through hyperedge HE-6 (induced by source paper "secure polar coding with delayed wiretapping information"):
  with members:
    - "secure polar coding for the two way wiretap channel"
    - "finite state markov wiretap channel with delayed feedback"
    - "achieving secrecy capacity of the wiretap channel and broadcast channel with a confidential component"
    - "polar coding for the broadcast channel with confidential messages a random binning analogy"
    - "polar coding for the general wiretap channel"
    - "secrecy results for compound wiretap channels"
    - "polar coding for secret key generation"

Connected through hyperedge HE-7 (induced by source paper "systematic convolutional low density generator matrix code"):
  with members:
    - "systematic block markov superposition transmission of repetition codes"
    - "threshold saturation for spatially coupled ldpc and ldgm codes on bms channels"
    - "block markov superposition transmission construction of big convolutional codes from short codes"
    - "spatially coupled ensembles universally achieve capacity under belief propagation"
    - "threshold saturation via spatial coupling why convolutional ldpc ensembles perform so well over the bec"
    - "threshold saturation on bms channels via spatial coupling"

Connected through hyperedge HE-8 (induced by source paper "secure polar coding for adversarial wiretap channel"):
  with members:
    - "polar coding for non stationary channels"
    - "achieving secrecy capacity of the wiretap channel and broadcast channel with a confidential component"
    - "polar coding for the broadcast channel with confidential messages a random binning analogy"
    - "polar coding for the general wiretap channel"
    - "achieving the secrecy capacity of wiretap channels using 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)