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 "part i improving computational efficiency of communication for omniscience"):
  Abstract: Communication for omniscience (CO) refers to the problem where the users in a finite set $V$ observe a discrete multiple random source and want to exchange data over broadcast channels to reach omniscience, the state where everyone recovers the entire source. This paper studies how to improve the computational complexity for the problem of minimizing the sum-rate for attaining omniscience in $V$. While the existing algorithms rely on the submodular function minimization (SFM) techniques and complete in $O(|V|^2 \cdot \text{SFM}(|V|)$ time, we prove the strict strong map property of the nesting SFM problem. We propose a parametric (PAR) algorithm that utilizes the parametric SFM techniques and reduce the the complexity to $O(|V| \cdot \text{SFM}(|V|)$. The output of the PAR algorithm is in fact the segmented Dilworth truncation of the residual entropy for all minimum sum-rate estimates $\alpha$, which characterizes the principal sequence of partitions (PSP) and solves some related problems: It not only determines the secret capacity, a dual problem to CO, and the network strength of a graph, but also outlines the hierarchical solution to a combinatorial clustering problem. \end{abstract}

Includes members:
  Member "part ii a practical approach for successive omniscience":
    also connected through other hyperedges:
      (none)
  Member "improving computational efficiency of communication for omniscience and successive omniscience":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "part ii a practical approach for successive omniscience")
  Member "secret key agreement under discussion rate constraints":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "secret key agreement for hypergraphical sources with limited total discussion")
  Member "a faster algorithm for asymptotic communication for omniscience":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "part ii a practical approach for successive omniscience")
  Member "info clustering a mathematical theory for data clustering":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "secret key agreement for hypergraphical sources with limited total discussion")
  Member "on the public communication needed to achieve sk capacity in the multiterminal source model":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "communication for generating correlation a unifying survey")
  Member "efficient algorithms for the data exchange problem":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "part ii a practical approach for successive omniscience")
  Member "coded cooperative data exchange in multihop networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "part ii a practical approach for successive omniscience")

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)