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 "a faster algorithm for asymptotic communication for omniscience"):
  Abstract: We propose a modified decomposition algorithm (MDA) to solve the asymptotic communication for omniscience (CO) problem where the communication rates could be real or fractional. By starting with a lower estimation of the minimum sum-rate, the MDA algorithm iteratively updates the estimation by the optimizer of a Dilworth truncation problem until the minimum is reached with a corresponding optimal rate vector. We also propose a fusion method implementation of the coordinate-wise saturation capacity algorithm (CoordSatCapFus) for solving the Dilworth truncation problem, where the minimization is done over a fused user set with a cardinality smaller than the original one. We show that the MDA algorithm is less complex than the existing ones. In addition, we show that the non-asymptotic CO problem, where the communication rates are integral, can be solved by one more call of the CoordSatCapfus algorithm. By choosing a proper linear ordering of the user indices in the MDA algorithm, the optimal rate vector is also the one with the minimum weighted sum-rate.

Includes members:
  Member "info clustering a mathematical theory for data clustering":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "secret key agreement for hypergraphical sources with limited total discussion")
  Member "a game theoretic perspective on communication for omniscience":
    also connected through other hyperedges:
      - Hyperedge HE-2 (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-3 (induced by source paper "communication for omniscience")
  Member "iterative merging algorithm for cooperative data exchange":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "part ii a practical approach for successive omniscience")
  Member "fairest constant sum rate transmission for cooperative data exchange an m convex minimization approach":
    also connected through other hyperedges:
      - Hyperedge HE-5 (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-6 (induced by source paper "part i improving computational efficiency of communication for omniscience")
  Member "coded cooperative data exchange in multihop networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (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-8 (induced by source paper "embedded index coding")

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)