human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "entropy power inequality for a family of discrete random variables"):
  Abstract: It is known that the Entropy Power Inequality (EPI) always holds if the random variables have density. Not much work has been done to identify discrete distributions for which the inequality holds with the differential entropy replaced by the discrete entropy. Harremoes and Vignat showed that it holds for the pair (B(m, p),B(n, p)), m, n ∈ ℕ, (where B(n, p) is a Binomial distribution with n trials each with success probability p) for p = 0.5. In this paper, we considerably expand the set of Binomial distributions for which the inequality holds and, in particular, identify n 0 (p) such that for all m, n ≥ n 0 (p), the EPI holds for (B(m, p),B(n, p)). We further show that the EPI holds for the discrete random variables that can be expressed as the sum of n independent and identically distributed (IID) discrete random variables for large n.

Includes members:
  Member "monotonicity thinning and discrete versions of the entropy power inequality":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "an entropy power inequality for discrete random variables")
  Member "thinning entropy and the law of thin numbers":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a de bruijn identity for discrete random variables")
  Member "monotonic convergence in an information theoretic law of small numbers":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "forward and reverse entropy power inequalities in convex geometry")
  Member "generalized entropy power inequalities and monotonicity properties of information":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "two remarks on generalized entropy power inequalities")
  Member "mutual information and minimum mean square error in gaussian channels":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "on the information bottleneck problems models connections applications and information theoretic views")

Question: Please tell me which class the source paper 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)