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: "the shannon lower bound is asymptotically tight"
  Abstract: The  Shannon lower bound  is one of the few lower bounds on the rate-distortion function that holds for a large class of sources. In this paper, which considers exclusively norm-based difference distortion measures, it is demonstrated that its gap to the rate-distortion function vanishes as the allowed distortion tends to zero for all sources having finite differential entropy and whose integer part has finite entropy. Conversely, it is demonstrated that if the integer part of the source has infinite entropy, then its rate-distortion function is infinite for every finite distortion level. Thus, the Shannon lower bound provides an asymptotically tight bound on the rate-distortion function if, and only if, the integer part of the source has finite entropy.

Connected through hyperedge HE-1 (induced by source paper "the ceo problem with rth power of difference and logarithmic distortions"):
  with members:
    - "remote source coding under gaussian noise dueling roles of power and entropy power"
    - "universality of logarithmic loss in lossy compression"
    - "the non regular ceo problem"
    - "network compression worst case analysis"
    - "an outer bound for the vector gaussian ceo problem"
    - "multiterminal source coding under logarithmic loss"
    - "successive wyner ziv coding scheme and its application to the quadratic gaussian ceo problem"
    - "mutual information and minimum mean square error in gaussian channels"

Connected through hyperedge HE-2 (induced by source paper "a lower bound on the differential entropy of log concave random vectors with applications"):
  with members:
    - "forward and reverse entropy power inequalities in convex geometry"
    - "wasserstein stability of the entropy power inequality for log concave densities"
    - "links between the logarithmic sobolev inequality and the convolution inequalities for entropy and fisher information"
    - "a concavity property for the reciprocal of fisher information and its consequences on costa s epi"
    - "entropy bounds on abelian groups and the ruzsa divergence"
    - "data compression with low distortion and finite blocklength"
    - "a strengthened entropy power inequality for log concave densities"
    - "the entropy per coordinate of a random vector is highly constrained under convexity conditions"

Connected through hyperedge HE-3 (induced by source paper "rate distortion theory of finite point processes"):
  with members:
    - "compressing sets and multisets of sequences"
    - "covering point patterns"
    - "benefiting from disorder source coding for unordered data"

Connected through hyperedge HE-4 (induced by source paper "rate distortion theory for general sets and measures"):
  with members:
    - "entropy and source coding for integer dimensional singular random variables"
    - "information theoretic limits of matrix completion"

Connected through hyperedge HE-5 (induced by source paper "on the information dimension of stochastic processes"):
  with members:
    - "compression based compressed sensing"
    - "degrees of freedom in vector interference channels"
    - "universal compressed sensing"
    - "optimal phase transitions in compressed sensing"

Connected through hyperedge HE-6 (induced by source paper "on the information dimension of multivariate gaussian processes"):
  with members:
    - "on the information dimension of stochastic processes"
    - "degrees of freedom in vector interference channels"

Connected through hyperedge HE-7 (induced by source paper "data compression with low distortion and finite blocklength"):
  with members:
    - "converse bounds for entropy constrained quantization via a variational entropy inequality"
    - "wasserstein continuity of entropy and outer bounds for interference channels"
    - "fixed length lossy compression in the finite blocklength regime"

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)