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 "a concavity property for the reciprocal of fisher information and its consequences on costa s epi"):
  Abstract: We prove that the reciprocal of Fisher information of a log-concave probability density X in Rn is concave in t with respect to the addition of a Gaussian noise Zt=N(0,tIn). As a byproduct of this result we show that the third derivative of the entropy power of a log-concave probability density X in Rn is nonnegative in t with respect to the addition of a Gaussian noise Zt. For log-concave densities this improves the well-known Costa’s concavity property of the entropy power (Costa, 1985).

Includes members:
  Member "a strengthened entropy power inequality for log concave densities":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a lower bound on the differential entropy of log concave random vectors with applications")
  Member "higher order derivatives in costa s entropy power inequality":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "convexity of mutual information along the ornstein uhlenbeck flow")
  Member "the concavity of renyi entropy power":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "transportation proofs of r enyi entropy power inequalities")
  Member "an information theoretic proof of nash s inequality":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "variants of the entropy power inequality")
  Member "information theoretic proofs of entropy power inequalities":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "vector gaussian successive refinement with degraded side information")
  Member "mutual information and minimum mean square error in gaussian channels":
    also connected through other hyperedges:
      - Hyperedge HE-6 (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)