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 "coarse graining and the blackwell order"):
  Abstract: Suppose we have a pair of information channels,      κ 1  ,  κ 2     , with a common input. The Blackwell order is a partial order over channels that compares     κ 1     and     κ 2     by the maximal expected utility an agent can obtain when decisions are based on the channel outputs. Equivalently,     κ 1     is said to be Blackwell-inferior to     κ 2     if and only if     κ 1     can be constructed by garbling the output of     κ 2    . A related partial order stipulates that     κ 2     is more capable than     κ 1     if the mutual information between the input and output is larger for     κ 2     than for     κ 1     for any distribution over inputs. A Blackwell-inferior channel is necessarily less capable. However, examples are known where     κ 1     is less capable than     κ 2     but not Blackwell-inferior. We show that this may even happen when     κ 1     is constructed by coarse-graining the inputs of     κ 2    . Such a coarse-graining is a special kind of “pre-garbling” of the channel inputs. This example directly establishes that the expected value of the shared utility function for the coarse-grained channel is larger than it is for the non-coarse-grained channel. This contradicts the intuition that coarse-graining can only destroy information and lead to inferior channels. We also discuss our results in the context of information decompositions.

Includes members:
  Member "on extractable shared information":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "generalised measures of multivariate information content")
  Member "quantifying unique information":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "an operational information decomposition via synergistic disclosure")

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)