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: "perfect sampling of graph k colorings for k o delta 2"
  Abstract: We give an algorithm for perfect sampling from the uniform distribution on proper $k$-colorings of graphs of maximum degree $\Delta$, which, for $\Delta \in [17, \log n]$, terminates with a sample in expected time $\mathrm{poly}(n)$ time whenever $k >\frac{2e\Delta^2}{\log \Delta}$ (here, $n$ is the number of vertices in the graph). To the best of our knowledge, this is the first perfect sampling algorithm for proper $k$-colorings that provably terminates in expected polynomial time while requiring only $k=o(\Delta^2)$ colors in general. #R##N#Inspired by the \emph{bounding chain} approach pioneered independently by Haggstrom \& Nelander~(Scand. J. Statist., 1999) and Huber~(STOC 1998) (who used the approach to give a perfect sampling algorithm requiring $k >\Delta^2 + 2\Delta$ for its expected running time to be a polynomial), our algorithm is based on a novel bounding chain for the coloring problem.

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)