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: "a ptas for the steiner forest problem in doubling metrics"
  Abstract: We achieve a (randomized) polynomial-time approximation scheme (PTAS) for the Steiner Forest Problem in doubling metrics. Before our work, a PTAS is given only for the Euclidean plane in [FOCS 2008: Borradaile, Klein and Mathieu]. Our PTAS also shares similarities with the dynamic programming for sparse instances used in [STOC 2012: Bartal, Gottlieb and Krauthgamer] and [SODA 2016: Chan and Jiang]. However, extending previous approaches requires overcoming several non-trivial hurdles, and we make the following technical contributions. #R##N#(1) We prove a technical lemma showing that Steiner points have to be "near" the terminals in an optimal Steiner tree. This enables us to define a heuristic to estimate the local behavior of the optimal solution, even though the Steiner points are unknown in advance. This lemma also generalizes previous results in the Euclidean plane, and may be of independent interest for related problems involving Steiner points. #R##N#(2) We develop a novel algorithmic technique known as "adaptive cells" to overcome the difficulty of keeping track of multiple components in a solution. Our idea is based on but significantly different from the previously proposed "uniform cells" in the FOCS 2008 paper, whose techniques cannot be readily applied to doubling metrics.

Connected through hyperedge HE-1 (induced by source paper "near linear time approximation schemes for steiner tree and forest in low dimensional spaces"):
  with members:
    - "greedy spanners are optimal in doubling metrics"
    - "the greedy spanner is existentially optimal"
    - "the traveling salesman problem low dimensionality implies a polynomial time approximation scheme"
    - "a light metric spanner"
    - "a polynomial time approximation scheme for euclidean steiner forest"
    - "an efficient polynomial time approximation scheme for steiner forest in planar graphs"
    - "approximation schemes for steiner forest on planar graphs and graphs of bounded treewidth"
    - "fast construction of nets in low dimensional metrics and their applications"

Connected through hyperedge HE-2 (induced by source paper "near linear time approximation schemes for clustering in doubling metrics"):
  with members:
    - "travelling on graphs with small highway dimension"
    - "the parameterized hardness of the k center problem in transportation networks"
    - "approximation schemes for capacitated clustering in doubling metrics"
    - "a fast approximation scheme for low dimensional k means"
    - "approximation schemes for clustering with outliers"
    - "constant approximation for k median and k means with outliers via iterative rounding"
    - "better guarantees for k means and euclidean k median by primal dual algorithms"
    - "local search yields a ptas for k means in doubling metrics"

Connected through hyperedge HE-3 (induced by source paper "varepsilon coresets for clustering with outliers in doubling metrics"):
  with members:
    - "turning big data into tiny data constant size coresets for k means pca and projective clustering"
    - "clustering high dimensional dynamic data streams"
    - "coresets and sketches"
    - "new frameworks for offline and streaming coreset constructions"
    - "local search yields a ptas for k means in doubling metrics"
    - "the traveling salesman problem low dimensionality implies a polynomial time approximation scheme"
    - "from hierarchical partitions to hierarchical covers optimal fault tolerant spanners for doubling metrics"
    - "a unified framework for approximating and clustering data"

Connected through hyperedge HE-4 (induced by source paper "a unified ptas for prize collecting tsp and steiner tree problem in doubling metrics"):
  with members:
    - "the traveling salesman problem low dimensionality implies a polynomial time approximation scheme"
    - "a polynomial time approximation scheme for euclidean steiner forest"
    - "combining approximation algorithms for the prize collecting tsp"

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)