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 "mutual information bounds via adjacency events"):
  Abstract: The mutual information between two jointly distributed random variables    $X$    and    $Y$    is a functional of the joint distribution    $P_{XY}$   , which is sometimes difficult to handle or estimate. A coarser description of the statistical behavior of    $(X,Y)$    is given by the marginal distributions    $P_{X}, P_{Y}$    and the  adjacency  relation induced by the joint distribution, where    $x$    and    $y$    are adjacent if    $P(x,y)>0$   . We derive a lower bound on the mutual information in terms of these entities. The bound is obtained by viewing the channel from    $X$    to    $Y$    as a probability distribution on a set of possible  actions , where an action determines the output for any possible input, and is independently drawn. We also provide an alternative proof based on convex optimization that yields a generally tighter bound. Finally, we derive an upper bound on the mutual information in terms of adjacency events between the action and the pair    $(X,Y)$   , where in this case, an action    $a$    and a pair    $(x,y)$    are adjacent if    $y=a(x)$   . As an example, we apply our bounds to the binary deletion channel and show that for the special case of an independent identically distributed input distribution and a range of deletion probabilities, our lower and upper bounds both outperform the best known bounds for the mutual information.

Includes members:
  Member "analysis of boolean functions":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "coarse grained complexity for dynamic algorithms")
  Member "bounds on the capacity of random insertion and deletion additive noise channels":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "an overview of capacity results for synchronization channels")

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)