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: "approximating capacitated k median with 1 epsilon k open facilities"
  Abstract: In the capacitated $k$-median (\CKM) problem, we are given a set $F$ of facilities, each facility $i \in F$ with a capacity $u_i$, a set $C$ of clients, a metric $d$ over $F \cup C$ and an integer $k$. The goal is to open $k$ facilities in $F$ and connect the clients $C$ to the open facilities such that each facility $i$ is connected by at most $u_i$ clients, so as to minimize the total connection cost. #R##N#In this paper, we give the first constant approximation for \CKM, that only violates the cardinality constraint by a factor of $1+\epsilon$. This generalizes the result of [Li15], which only works for the uniform capacitated case. Moreover, the approximation ratio we obtain is $O\big(\frac{1}{\epsilon^2}\log\frac1\epsilon\big)$, which is an exponential improvement over the ratio of $\exp(O(1/\epsilon^2))$ in [Li15]. The natural LP relaxation for the problem, which almost all previous algorithms for \CKM are based on, has unbounded integrality gap even if $(2-\epsilon)k$ facilities can be opened. We introduce a novel configuration LP for the problem, that overcomes this integrality gap.

Connected through hyperedge HE-1 (induced by source paper "generalized center problems with outliers"):
  with members:
    - "a lottery model for center type problems with outliers"
    - "the heterogeneous capacitated k center problem"
    - "the non uniform k center problem"
    - "on uniform capacitated k median beyond the natural lp relaxation"
    - "lp based algorithms for capacitated facility location"
    - "matroid and knapsack center problems"

Connected through hyperedge HE-2 (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"
    - "lp rounding for k centers with non uniform hard capacities"
    - "quasi polynomial local search for restricted max min fair allocation"
    - "approximability of capacitated network design"
    - "a new approximation technique for resource allocation problems"

Connected through hyperedge HE-3 (induced by source paper "an approximation algorithm for uniform capacitated k median problem with 1 epsilon capacity violation"):
  with members:
    - "on uniform capacitated k median beyond the natural lp relaxation"
    - "an improved approximation for k median and positive correlation in budgeted optimization"
    - "lp based algorithms for capacitated facility location"
    - "approximation algorithms for hard capacitated k facility location problems"
    - "bi factor approximation algorithms for hard capacitated k median problems"
    - "approximating k median via pseudo approximation"

Connected through hyperedge HE-4 (induced by source paper "on uniform capacitated k median beyond the natural lp relaxation"):
  with members:
    - "an improved approximation algorithm for the hard uniform capacitated k median problem"
    - "an improved approximation for k median and positive correlation in budgeted optimization"
    - "lp based algorithms for capacitated facility location"
    - "approximation algorithms for hard capacitated k facility location problems"
    - "bi factor approximation algorithms for hard capacitated k median problems"
    - "approximating k median via pseudo approximation"
    - "an optimal bifactor approximation algorithm for the metric uncapacitated facility location problem"
    - "greedy facility location algorithms analyzed using dual fitting with factor revealing lp"

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)