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 "extropy complementary dual of entropy"):
  Abstract: This article provides a completion to theories of information#R##N#based on entropy, resolving a longstanding question in its axiomatization as#R##N#proposed by Shannon and pursued by Jaynes. We show that Shannon’s entropy#R##N#function has a complementary dual function which we call “extropy.”#R##N#The entropy and the extropy of a binary distribution are identical. However,#R##N#the measure bifurcates into a pair of distinct measures for any quantity that is#R##N#not merely an event indicator. As with entropy, the maximum extropy distribution#R##N#is also the uniform distribution, and both measures are invariant with#R##N#respect to permutations of their mass functions. However, they behave quite#R##N#differently in their assessments of the refinement of a distribution, the axiom#R##N#which concerned Shannon and Jaynes. Their duality is specified via the relationship#R##N#among the entropies and extropies of course and fine partitions. We#R##N#also analyze the extropy function for densities, showing that relative extropy#R##N#constitutes a dual to the Kullback–Leibler divergence, widely recognized as#R##N#the continuous entropy measure. These results are unified within the general#R##N#structure of Bregman divergences. In this context they identify half the L2#R##N#metric as the extropic dual to the entropic directed distance. We describe a#R##N#statistical application to the scoring of sequential forecast distributions which#R##N#provoked the discovery.

Includes members:
  Member "the bethe permanent of a nonnegative matrix":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "gauges loops and polynomials for partition functions of graphical models")
  Member "on bregman distances and divergences of probability measures":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "bayesian inference with posterior regularization and applications to infinite latent svms")

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)