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: "fast rendezvous with advice"
  Abstract: Two mobile agents, starting from different nodes of an $n$-node network at possibly different times, have to meet at the same node. This problem is known as rendezvous. Agents move in synchronous rounds using a deterministic algorithm. In each round, an agent decides to either remain idle or to move to one of the adjacent nodes. Each agent has a distinct integer label from the set $\{1,...,L\}$, which it can use in the execution of the algorithm, but it does not know the label of the other agent. #R##N#If $D$ is the distance between the initial positions of the agents, then $\Omega(D)$ is an obvious lower bound on the time of rendezvous. However, if each agent has no initial knowledge other than its label, time $O(D)$ is usually impossible to achieve. We study the minimum amount of information that has to be available a priori to the agents to achieve rendezvous in optimal time $\Theta(D)$. This information is provided to the agents at the start by an oracle knowing the entire instance of the problem, i.e., the network, the starting positions of the agents, their wake-up rounds, and both of their labels. The oracle helps the agents by providing them with the same binary string called advice, which can be used by the agents during their navigation. The length of this string is called the size of advice. Our goal is to find the smallest size of advice which enables the agents to meet in time $\Theta(D)$. We show that this optimal size of advice is $\Theta(D\log(n/D)+\log\log L)$. The upper bound is proved by constructing an advice string of this size, and providing a natural rendezvous algorithm using this advice that works in time $\Theta(D)$ for all networks. The matching lower bound, which is the main contribution of this paper, is proved by exhibiting classes of networks for which it is impossible to achieve rendezvous in time $\Theta(D)$ with smaller advice.

Connected through hyperedge HE-1 (induced by source paper "asynchronous approach in the plane a deterministic polynomial algorithm"):
  with members:
    - "rendezvous in networks in spite of delay faults"
    - "byzantine gathering in networks"
    - "getting close without touching near gathering for autonomous mobile robots"
    - "time versus cost tradeoffs for deterministic rendezvous in networks"
    - "mobile agents rendezvous in spite of a malicious agent"
    - "rendezvous of distance aware mobile agents in unknown graphs"
    - "how to meet asynchronously at polynomial cost"
    - "delays induce an exponential memory gap for rendezvous in trees"

Connected through hyperedge HE-2 (induced by source paper "byzantine gathering in networks"):
  with members:
    - "time versus cost tradeoffs for deterministic rendezvous in networks"
    - "rendezvous of distance aware mobile agents in unknown graphs"
    - "how to meet asynchronously at polynomial cost"
    - "delays induce an exponential memory gap for rendezvous in trees"
    - "anonymous meeting in networks"
    - "the gathering problem for two oblivious robots with unreliable compasses"
    - "how to meet asynchronously almost everywhere"

Connected through hyperedge HE-3 (induced by source paper "tradeoffs between cost and information for rendezvous and treasure hunt"):
  with members:
    - "time versus cost tradeoffs for deterministic rendezvous in networks"
    - "revisiting the problem of searching on a line"
    - "how to meet asynchronously at polynomial cost"
    - "faster treasure hunt and better strongly universal exploration sequences"
    - "how to meet asynchronously almost everywhere"

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)