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 "fairness in communication for omniscience"):
  Abstract: We consider the problem of how to fairly distribute the minimum sum-rate among the users in communication for omniscience (CO). We formulate a problem of minimizing a weighted quadratic function over a submodular base polyhedron which contains all achievable rate vectors, or transmission strategies, for CO that have the same sum-rate. By solving it, we can determine the rate vector that optimizes the Jain's fairness measure, a more commonly used fairness index than the Shapley value in communications engineering. We show that the optimizer is a lexicographically optimal (lex-optimal) base and can be determined by a decomposition algorithm (DA) that is based on submodular function minimization (SFM) algorithm and completes in strongly polynomial time. We prove that the lex-optimal minimum sum-rate strategy for CO can be determined by finding the lex-optimal base in each user subset in the fundamental partition and the complexity can be reduced accordingly.

Includes members:
  Member "a game theoretic perspective on communication for omniscience":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a monetary mechanism for stabilizing cooperative data exchange with selfish users")
  Member "estimating minimum sum rate for cooperative data exchange":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "communication for omniscience")
  Member "fairest constant sum rate transmission for cooperative data exchange an m convex minimization approach":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "attaining fairness in communication for omniscience")
  Member "efficient algorithms for the data exchange problem":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "part i improving computational efficiency of communication for omniscience")
  Member "structured convex optimization under submodular constraints":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "attaining fairness in communication for omniscience")
  Member "coded cooperative data exchange in multihop networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "part i improving computational efficiency of communication for omniscience")
  Member "on coding for cooperative data exchange":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "embedded index coding")
  Member "a quantitative measure of fairness and discrimination for resource allocation in shared computer systems":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "coexistence mechanism between embb and urllc in 5g wireless networks")

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)