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 "order optimal information spreading using algebraic gossip"):
  Abstract: In this paper we study gossip based information spreading with bounded message sizes. We use algebraic gossip to disseminate $k$ distinct messages to all $n$ nodes in a network. For arbitrary networks we provide a new upper bound for uniform algebraic gossip of $O((k+\log n + D)\Delta)$ rounds with high probability, where $D$ and $\Delta$ are the diameter and the maximum degree in the network, respectively. For many topologies and selections of $k$ this bound improves previous results, in particular, for graphs with a constant maximum degree it implies that uniform gossip is \emph{order optimal} and the stopping time is $\Theta(k + D)$. #R##N#To eliminate the factor of $\Delta$ from the upper bound we propose a non-uniform gossip protocol, TAG, which is based on algebraic gossip and an arbitrary spanning tree protocol $\S$. The stopping time of TAG is $O(k+\log n +d(\S)+t(\S))$, where $t(\S)$ is the stopping time of the spanning tree protocol, and $d(\S)$ is the diameter of the spanning tree. We provide two general cases in which this bound leads to an order optimal protocol. The first is for $k=\Omega(n)$, where, using a simple gossip broadcast protocol that creates a spanning tree in at most linear time, we show that TAG finishes after $\Theta(n)$ rounds for any graph. The second uses a sophisticated, recent gossip protocol to build a fast spanning tree on graphs with large weak conductance. In turn, this leads to the optimally of TAG on these graphs for $k=\Omega(\mathrm{polylog}(n))$. The technique used in our proofs relies on queuing theory, which is an interesting approach that can be useful in future gossip analysis.

Includes members:
  Member "tighter worst case bounds on algebraic gossip":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on the influence of graph density on randomized gossiping")
  Member "global computation in a poorly connected world fast rumor spreading with no dependence on conductance":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "message reduction in the local model is a free lunch")
  Member "bounds for algebraic gossip on graphs":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "analyzing network coding gossip made easy")
  Member "analyzing network coding gossip made easy":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "synchronous transmissions in low power wireless a survey of communication protocols and network services")
  Member "quasirandom rumor spreading":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "lower bounds for the happy coloring problems")

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)