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: "dynamic approximate maximum independent set of intervals hypercubes and hyperrectangles"
  Abstract: Independent set is a fundamental problem in combinatorial optimization. While in general graphs the problem is essentially inapproximable, for many important graph classes there are approximation algorithms known in the offline setting. These graph classes include interval graphs and geometric intersection graphs, where vertices correspond to intervals/geometric objects and an edge indicates that the two corresponding objects intersect. #R##N#We present dynamic approximation algorithms for independent set of intervals, hypercubes and hyperrectangles in $d$ dimensions. They work in the fully dynamic model where each update inserts or deletes a geometric object. All our algorithms are deterministic and have worst-case update times that are polylogarithmic for constant $d$ and $\epsilon> 0$, assuming that the coordinates of all input objects are in $[0, N]^d$ and each of their edges has length at least 1. We obtain the following results: #R##N#$\bullet$ For weighted intervals, we maintain a $(1+\epsilon)$-approximate solution. #R##N#$\bullet$ For $d$-dimensional hypercubes we maintain a $(1+\epsilon)2^{d}$-approximate solution in the unweighted case and a $O(2^{d})$-approximate solution in the weighted case. Also, we show that for maintaining an unweighted $(1+\epsilon)$-approximate solution one needs polynomial update time for $d\ge2$ if the ETH holds. #R##N#$\bullet$ For weighted $d$-dimensional hyperrectangles we present a dynamic algorithm with approximation ratio $(1+\epsilon)\log^{d-1}N$.

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.CG(Computational Geometry)