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 "on computation rates for arithmetic sum"):
  Abstract: For zero-error function computation over directed acyclic networks, existing upper and lower bounds on the computation capacity are known to be loose. In this work we consider the problem of computing the arithmetic sum over a specific directed acyclic network that is not a tree. We assume the sources to be i.i.d. Bernoulli with parameter $1/2$. Even in this simple setting, we demonstrate that upper bounding the computation rate is quite nontrivial. In particular, it requires us to consider variable length network codes and relate the upper bound to equivalently lower bounding the entropy of descriptions observed by the terminal conditioned on the function value. This lower bound is obtained by further lower bounding the entropy of a so-called \textit{clumpy distribution}. We also demonstrate an achievable scheme that uses variable length network codes and in-network compression.

Includes members:
  Member "sum networks from undirected graphs construction and capacity analysis":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "sum networks from incidence structures construction and capacity analysis")
  Member "capacity of sum networks for different message alphabets":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "coded caching schemes with reduced subpacketization from linear block codes")
  Member "upper bound on function computation in directed acyclic networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (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-4 (induced by source paper "linear network coding effects of varying the message dimension on the set of characteristics")
  Member "network coding for computing cut set bounds":
    also connected through other hyperedges:
      - Hyperedge HE-5 (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-6 (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-7 (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)