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 "improved upper bound on the network function computing capacity"):
  Abstract: The problem of network function computation over a directed acyclic network is investigated in this paper. In such a network, a sink node desires to compute with zero error a {\em target function}, of which the inputs are generated at multiple source nodes. The edges in the network are assumed to be error-free and have limited capacity. The nodes in the network are assumed to have unbounded computing capability and be able to perform network coding. The {\em computing rate} of a network code that can compute the target function over the network is the average number of times that the target function is computed with zero error for one use of the network. In this paper, we obtain an improved upper bound on the computing capacity, which is applicable to arbitrary target functions and arbitrary network topologies. This improved upper bound not only is an enhancement of the previous upper bounds but also is the first tight upper bound on the computing capacity for computing an arithmetic sum over a certain non-tree network, which has been widely studied in the literature. We also introduce a multi-dimensional array approach that facilitates evaluation of the improved upper bound. Furthermore, we apply this bound to the problem of computing a vector-linear function over a network. With this bound, we are able to not only enhance a previous result on computing a vector-linear function over a network but also simplify the proof significantly. Finally, we prove that for computing the binary maximum function over the reverse butterfly network, our improved upper bound is not achievable. This result establishes that in general our improved upper bound is non achievable, but whether it is asymptotically achievable or not remains open.

Includes members:
  Member "upper bound on function computation in directed acyclic networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "computing and communicating functions in disorganized wireless networks")
  Member "on network coding for sum networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "linear network coding effects of varying the message dimension on the set of characteristics")
  Member "computing linear functions by linear coding over networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "how to distribute computation in networks")
  Member "network coding for computing cut set bounds":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "expand and randomize an algebraic approach to secure computation")
  Member "optimal function computation in directed and undirected graphs":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "how to distribute computation in networks")
  Member "linear codes target function classes and network computing capacity":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "structured mappings and conferencing common information for multiple access channels")
  Member "on network functional compression":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "how to distribute computation in networks")
  Member "communicating the sum of sources over a network":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "two way function computation")

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)