human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "the heterogeneous capacitated k center problem"):
  Abstract: In this paper we initiate the study of the heterogeneous capacitated $k$-center problem: given a metric space $X = (F \cup C, d)$, and a collection of capacities. The goal is to open each capacity at a unique facility location in $F$, and also to assign clients to facilities so that the number of clients assigned to any facility is at most the capacity installed; the objective is then to minimize the maximum distance between a client and its assigned facility. If all the capacities $c_i$'s are identical, the problem becomes the well-studied uniform capacitated $k$-center problem for which constant-factor approximations are known. The additional choice of determining which capacity should be installed in which location makes our problem considerably different from this problem, as well the non-uniform generalizations studied thus far in literature. In fact, one of our contributions is in relating the heterogeneous problem to special-cases of the classical Santa Claus problem. Using this connection, and by designing new algorithms for these special cases, we get the following results: (a)A quasi-polynomial time $O(\log n/\epsilon)$-approximation where every capacity is violated by $1+\varepsilon$, (b) A polynomial time $O(1)$-approximation where every capacity is violated by an $O(\log n)$ factor. We get improved results for the {\em soft-capacities} version where we can place multiple facilities in the same location.

Includes members:
  Member "the non uniform k center problem":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "the effectiveness of johnson lindenstrauss transform for high dimensional optimization with outliers")
  Member "constant approximation for capacitated k median with 1 epsilon capacity violation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "fair clustering with multiple colors")
  Member "on uniform capacitated k median beyond the natural lp relaxation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "fair clustering with multiple colors")
  Member "lp based algorithms for capacitated facility location":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "easy capacitated facility location problems with connections to lot sizing")
  Member "approximating capacitated k median with 1 epsilon k open facilities":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "generalized center problems with outliers")
  Member "lp rounding for k centers with non uniform hard capacities":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "fair clustering with multiple colors")
  Member "quasi polynomial local search for restricted max min fair allocation":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "restricted max min allocation approximation and integrality gap")
  Member "approximability of capacitated network design":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "a tight algorithm for strongly connected steiner subgraph on two terminals with demands")

Question: Please tell me which class the source paper 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)