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 "capacity bounds for networks with correlated sources and characterisation of distributions by entropies"):
  Abstract: Characterising the capacity region for a network can be extremely difficult. Even with independent sources, determining the capacity region can be as hard as the open problem of characterising all information inequalities. The majority of computable outer bounds in the literature are relaxations of the Linear Programming bound which involves entropy functions of random variables related to the sources and link messages. When sources are not independent, the problem is even more complicated. Extension of Linear Programming bounds to networks with correlated sources is largely open. Source dependence is usually specified via a joint probability distribution, and one of the main challenges in extending linear program bounds is the difficulty (or impossibility) of characterising arbitrary dependencies via entropy functions. This paper tackles the problem by answering the question of how well entropy functions can characterise correlation among sources. We show that by using carefully chosen auxiliary random variables, the characterisation can be fairly "accurate" Using such auxiliary random variables we also give implicit and explicit outer bounds on the capacity of networks with correlated sources. The characterisation of correlation or joint distribution via Shannon entropy functions is also applicable to other information measures such as Renyi entropy and Tsallis entropy.

Includes members:
  Member "cut set bounds on network information flow":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on the capacity for distributed index coding")
  Member "characterising probability distributions via entropies":
    also connected through other hyperedges:
      (none)
  Member "beyond the cut set bound uncertainty computations in network coding with correlated sources":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "on the capacity of computation broadcast")
  Member "beyond the cut set bound uncertainty computations in network coding with correlated sources":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "on the capacity of computation broadcast")
  Member "network coding capacity a functional dependence bound":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a minimal set of shannon type inequalities for functional dependence structures")
  Member "dualities between entropy functions and network codes":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a local perspective on the edge removal problem")
  Member "network information flow with correlated sources":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "cut set bounds on network information flow")

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)