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: "approximability of capacitated network design"
  Abstract: In the {\em capacitated} survivable network design problem (Cap-SNDP), we are given an undirected multi-graph where each edge has a capacity and a cost. The goal is to find a minimum cost subset of edges that satisfies a given set of pairwise minimum-cut requirements. Unlike its classical special case of SNDP when all capacities are unit, the approximability of Cap-SNDP is not well understood; even in very restricted settings no known algorithm achieves a $o(m)$ approximation, where $m$ is the number of edges in the graph. In this paper, we obtain several new results and insights into the approximability of Cap-SNDP.

Connected through hyperedge HE-1 (induced by source paper "the heterogeneous capacitated k center problem"):
  with members:
    - "the non uniform k center problem"
    - "constant approximation for capacitated k median with 1 epsilon capacity violation"
    - "on uniform capacitated k median beyond the natural lp relaxation"
    - "lp based algorithms for capacitated facility location"
    - "approximating capacitated k median with 1 epsilon k open facilities"
    - "lp rounding for k centers with non uniform hard capacities"
    - "quasi polynomial local search for restricted max min fair allocation"
    - "a new approximation technique for resource allocation problems"

Connected through hyperedge HE-2 (induced by source paper "a tight algorithm for strongly connected steiner subgraph on two terminals with demands"):
  with members:
    - "optimal parameterized algorithms for planar facility location problems using voronoi diagrams"
    - "everything you always wanted to know about the parameterized complexity of subgraph isomorphism but were afraid to ask"

Connected through hyperedge HE-3 (induced by source paper "cluster before you hallucinate approximating node capacitated network design and energy efficient routing"):
  with members:
    - "an lmp o log n approximation algorithm for node weighted prize collecting steiner tree"
    - "online primal dual for non linear optimization with applications to speed scaling"
    - "spectral sparsification of graphs"
    - "an o k 3 log n approximation algorithm for vertex connectivity survivable network design"

Connected through hyperedge HE-4 (induced by source paper "power efficient assignment of virtual machines to physical machines"):
  with members:
    - "online primal dual for non linear optimization with applications to speed scaling"
    - "optimal placement algorithms for virtual machines"

Connected through hyperedge HE-5 (induced by source paper "an lp with integrality gap 1 epsilon for multidimensional knapsack"):
  with members:
    - "on column restricted and priority covering integer programs"
    - "integrality gaps of linear and semi definite programming relaxations for knapsack"
    - "approximability of sparse integer programs"
    - "dependent randomized rounding for matroid polytopes and applications"

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)