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 convergence properties of shannon entropy"
  Abstract: Convergence properties of Shannon entropy are studied. In the differential setting, it is known that weak convergence of probability measures (convergence in distribution) is not sufficient for convergence of the associated differential entropies. In that direction, an interesting example is introduced and discussed in light of new general results provided here for the desired differential entropy convergence, which take into account both compactly and uncompactly supported densities. Convergence of differential entropy is also characterized in terms of the Kullback-Liebler discriminant for densities with fairly general supports, and it is shown that convergence in variation of probability measures guarantees such convergence under an appropriate boundedness condition on the densities involved. Results for the discrete setting are also provided, allowing for infinitely supported probability measures, by taking advantage of the equivalence between weak convergence and convergence in variation in that setting.

Connected through hyperedge HE-1 (induced by source paper "phase transitions optimal errors and optimality of message passing in generalized linear models"):
  with members:
    - "the layered structure of tensor estimation and its mutual information"
    - "the replica symmetric prediction for compressed sensing with gaussian matrices is exact"
    - "proof of threshold saturation for spatially coupled sparse superposition codes"
    - "statistical physics and approximate message passing algorithms for sparse linear estimation problems in signal processing and coding theory"
    - "binary linear classification and feature selection via generalized approximate message passing"
    - "spectral redemption in clustering sparse networks"
    - "expectation maximization gaussian mixture approximate message passing"
    - "simultaneously structured models with application to sparse and low rank matrices"

Connected through hyperedge HE-2 (induced by source paper "existence and continuity of differential entropy for a class of distributions"):
  with members:
    - "on reverse pinsker inequalities"
    - "wasserstein continuity of entropy and outer bounds for interference channels"

Connected through hyperedge HE-3 (induced by source paper "shannon entropy estimation in alphabets from convergence results"):
  with members:
    - "minimax estimation of functionals of discrete distributions"
    - "minimax rates of entropy estimation on large alphabets via best polynomial approximation"

Connected through hyperedge HE-4 (induced by source paper "on the finiteness of the capacity of continuous channels"):
  with members:
    - "information theoretic proofs of entropy power inequalities"

Connected through hyperedge HE-5 (induced by source paper "achievable secrecy rates over mimome gaussian channels with gmm signals in low noise regime"):
  with members:
    - "secret message transmission by harq with multiple encoding"
    - "secret sharing ldpc codes for the bpsk constrained gaussian wiretap channel"
    - "a compressed sensing wire tap channel"
    - "rethinking the secrecy outage formulation a secure transmission design perspective"
    - "mimo wiretap channels with arbitrarily varying eavesdropper channel states"
    - "secure transmission with multiple antennas ii the mimome wiretap channel"

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)