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: "an exponential lower bound for cut sparsifiers in planar graphs"
  Abstract: Given an edge-weighted graph $G$ with a set $Q$ of $k$ terminals, a mimicking network is a graph with the same set of terminals that exactly preserves the sizes of minimum cuts between any partition of the terminals. A natural question in the area of graph compression is to provide as small mimicking networks as possible for input graph $G$ being either an arbitrary graph or coming from a specific graph class. #R##N#In this note we show an exponential lower bound for cut mimicking networks in planar graphs: there are edge-weighted planar graphs with $k$ terminals that require $2^{k-2}$ edges in any mimicking network. This nearly matches an upper bound of $O(k 2^{2k})$ of Krauthgamer and Rika [SODA 2013, arXiv:1702.05951] and is in sharp contrast with the $O(k^2)$ upper bound under the assumption that all terminals lie on a single face [Goranci, Henzinger, Peng, arXiv:1702.01136]. As a side result we show a hard instance for the double-exponential upper bounds given by Hagerup, Katajainen, Nishimura, and Ragde~[JCSS 1998], Khan and Raghavendra~[IPL 2014], and Chambers and Eppstein~[JGAA 2013].

Connected through hyperedge HE-1 (induced by source paper "a face cover perspective to ell_1 embeddings of planar graphs"):
  with members:
    - "flow cut gaps and face covers in planar graphs"
    - "nearly eth tight algorithms for planar steiner tree with terminals on few faces"
    - "metric embedding via shortest path decompositions"
    - "refined vertex sparsifiers of planar graphs"
    - "on notions of distortion and an almost minimum spanning tree with constant average distortion"
    - "vertex sparsifiers new results from old techniques"
    - "cops robbers and threatening skeletons padded decomposition for minor free graphs"
    - "flow cut gaps for integer and fractional multiflows"

Connected through hyperedge HE-2 (induced by source paper "mimicking networks parameterized by connectivity"):
  with members:
    - "survivable network design for group connectivity in low treewidth graphs"
    - "improved guarantees for vertex sparsification in planar graphs"
    - "vertex sparsifiers new results from old techniques"
    - "mimicking networks and succinct representations of terminal cuts"

Connected through hyperedge HE-3 (induced by source paper "refined vertex sparsifiers of planar graphs"):
  with members:
    - "relaxed voronoi a simple framework for terminal clustering problems"
    - "steiner point removal with distortion o log k"
    - "improved guarantees for vertex sparsification in planar graphs"
    - "steiner point removal distant terminals don t really bother"
    - "graph minors for preserving terminal distances approximately lower and upper bounds"
    - "vertex sparsifiers new results from old techniques"
    - "on vertex sparsifiers with steiner nodes"
    - "mimicking networks and succinct representations of terminal cuts"

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)