human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "optimal gossip with direct addressing"
  Abstract: Gossip algorithms spread information by having nodes repeatedly forward information to a few random contacts. By their very nature, gossip algorithms tend to be distributed and fault tolerant. If done right, they can also be fast and message-efficient. A common model for gossip communication is the random phone call model, in which in each synchronous round each node can PUSH or PULL information to or from a random other node. For example, Karp et al. [FOCS 2000] gave algorithms in this model that spread a message to all nodes in $\Theta(\log n)$ rounds while sending only $O(\log \log n)$ messages per node on average. #R##N#Recently, Avin and Els\"asser [DISC 2013], studied the random phone call model with the natural and commonly used assumption of direct addressing. Direct addressing allows nodes to directly contact nodes whose ID (e.g., IP address) was learned before. They show that in this setting, one can "break the $\log n$ barrier" and achieve a gossip algorithm running in $O(\sqrt{\log n})$ rounds, albeit while using $O(\sqrt{\log n})$ messages per node. #R##N#We study the same model and give a simple gossip algorithm which spreads a message in only $O(\log \log n)$ rounds. We also prove a matching $\Omega(\log \log n)$ lower bound which shows that this running time is best possible. In particular we show that any gossip algorithm takes with high probability at least $0.99 \log \log n$ rounds to terminate. Lastly, our algorithm can be tweaked to send only $O(1)$ messages per node on average with only $O(\log n)$ bits per message. Our algorithm therefore simultaneously achieves the optimal round-, message-, and bit-complexity for this setting. As all prior gossip algorithms, our algorithm is also robust against failures. In particular, if in the beginning an oblivious adversary fails any $F$ nodes our algorithm still, with high probability, informs all but $o(F)$ surviving nodes.

Connected through hyperedge HE-1 (induced by source paper "consensus needs broadcast in noiseless models but can be exponentially easier in the presence of noise"):
  with members:
    - "ignore or comply on breaking symmetry in consensus"
    - "tight analysis for the 3 majority consensus dynamics"
    - "a tight analysis of the parallel undecided state dynamics with two colors"
    - "distributed computing with channel noise"
    - "breaking the log n barrier on rumor spreading"
    - "stabilizing consensus with many opinions"
    - "noisy rumor spreading and plurality consensus"
    - "the power of two choices in distributed voting"

Connected through hyperedge HE-2 (induced by source paper "optimal epidemic dissemination"):
  with members:
    - "simple and optimal randomized fault tolerant rumor spreading"
    - "asymptotically optimal randomized rumor spreading"
    - "gossip algorithms for distributed signal processing"

Connected through hyperedge HE-3 (induced by source paper "slow links fast links and the cost of gossip"):
  with members:
    - "rumor spreading with bounded in degree"
    - "radio network lower bounds made easy"
    - "simple fast and deterministic gossip and rumor spreading"
    - "global computation in a poorly connected world fast rumor spreading with no dependence on conductance"
    - "the impact of mobility on gossip algorithms"

Connected through hyperedge HE-4 (induced by source paper "gossiping with latencies"):
  with members:
    - "rumor spreading with bounded in degree"
    - "radio network lower bounds made easy"
    - "simple fast and deterministic gossip and rumor spreading"
    - "global computation in a poorly connected world fast rumor spreading with no dependence on conductance"
    - "the impact of mobility on gossip algorithms"

Connected through hyperedge HE-5 (induced by source paper "breaking the log n barrier on rumor spreading"):
  with members:
    - "simple fast and deterministic gossip and rumor spreading"
    - "global computation in a poorly connected world fast rumor spreading with no dependence on conductance"
    - "quasirandom rumor spreading"

Connected through hyperedge HE-6 (induced by source paper "breathe before speaking efficient information dissemination despite noisy limited and anonymous communication"):
  with members:
    - "the power of two choices in distributed voting"
    - "simple dynamics for plurality consensus"
    - "memory lower bounds for randomized collaborative search and applications to biology"
    - "collaborative search on the plane without communication"
    - "beeping a maximal independent set"
    - "simple fast and deterministic gossip and rumor spreading"
    - "global computation in a poorly connected world fast rumor spreading with no dependence on conductance"
    - "natural models for evolution on networks"

Connected through hyperedge HE-7 (induced by source paper "simple fast and deterministic gossip and rumor spreading"):
  with members:
    - "tight bounds for rumor spreading with vertex expansion"
    - "global computation in a poorly connected world fast rumor spreading with no dependence on conductance"
    - "analyzing network coding gossip made easy"
    - "quasirandom rumor spreading"

Connected through hyperedge HE-8 (induced by source paper "analyzing network coding gossip made easy"):
  with members:
    - "broadcast throughput in radio networks routing vs network coding"
    - "tight bounds for rumor spreading with vertex expansion"
    - "fast structuring of radio networks large for multi message communications"
    - "lower bounds on information dissemination in dynamic networks"
    - "bounded contention coding for wireless networks in the high snr regime"
    - "tighter worst case bounds on algebraic gossip"
    - "simple fast and deterministic gossip and rumor spreading"
    - "network coded gossip with correlated data"

Question: Please tell me which class the center node 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.DS(Data Structures and Algorithms)