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 "on uniform capacitated k median beyond the natural lp relaxation"):
  Abstract: In this paper, we study the uniform capacitated $k$-median problem. Obtaining a constant approximation algorithm for this problem is a notorious open problem; most previous works gave constant approximations by either violating the capacity constraints or the cardinality constraint. Notably, all these algorithms are based on the natural LP-relaxation for the problem. The LP-relaxation has unbounded integrality gap, even when we are allowed to violate the capacity constraints or the cardinality constraint by a factor of $2-\epsilon$. #R##N#Our result is an $\exp(O(1/\epsilon^2))$-approximation algorithm for the problem that violates the cardinality constraint by a factor of $1+\epsilon$. This is already beyond the capability of the natural LP relaxation, as it has unbounded integrality gap even if we are allowed to open $(2-\epsilon)k$ facilities. Indeed, our result is based on a novel LP for this problem. #R##N#The version as we described is the hard-capacitated version of the problem, as we can only open one facility at each location. This is as opposed to the soft-capacitated version, in which we are allowed to open more than one facilities at each location. We give a simple proof that in the uniform capacitated case, the soft-capacitated version and the hard-capacitated version are actually equivalent, up to a small constant loss in the approximation ratio.

Includes members:
  Member "an improved approximation algorithm for the hard uniform capacitated k median problem":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "improved local search based approximation algorithm for hard uniform capacitated k median problem")
  Member "an improved approximation for k median and positive correlation in budgeted optimization":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "individual fairness for k clustering")
  Member "lp based algorithms for capacitated facility location":
    also connected through other hyperedges:
      - Hyperedge HE-3 (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-4 (induced by source paper "generalized center problems with outliers")
  Member "approximation algorithms for hard capacitated k facility location problems":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "facility location problem with capacity constraints algorithmic and mechanism design perspectives")
  Member "bi factor approximation algorithms for hard capacitated k median problems":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "reconciliation k median clustering with non polarized representatives")
  Member "approximating k median via pseudo approximation":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "fair correlation clustering")
  Member "an optimal bifactor approximation algorithm for the metric uncapacitated facility location problem":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "constant factor approximation algorithms for parity constrained facility location problems")

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)