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: "on the configuration lp of the restricted assignment problem"
  Abstract: We consider the classical problem of Scheduling on Unrelated Machines. In this problem a set of jobs is to be distributed among a set of machines and the maximum load (makespan) is to be minimized. The processing time $p_{ij}$ of a job $j$ depends on the machine $i$ it is assigned to. Lenstra, Shmoys and Tardos gave a polynomial time $2$-approximation for this problem. In this paper we focus on a prominent special case, the Restricted Assignment problem, in which $p_{ij}\in\{p_j,\infty\}$. The configuration-LP is a linear programming relaxation for the Restricted Assignment problem. It was shown by Svensson that the multiplicative gap between integral and fractional solution, the integrality gap, is at most $2 - 1/17 \approx 1.9412$. In this paper we significantly simplify his proof and achieve a bound of $2 - 1/6 \approx 1.8333$. As a direct consequence this provides a polynomial $(2 - 1/6 + \epsilon)$-estimation algorithm for the Restricted Assignment problem by approximating the configuration-LP. The best lower bound known for the integrality gap is $1.5$ and no estimation algorithm with a guarantee better than $1.5$ exists unless $\mathrm{P} = \mathrm{NP}$.

Connected through hyperedge HE-1 (induced by source paper "simpler and better algorithms for minimum norm load balancing"):
  with members:
    - "approximation algorithms for minimum norm and ordered optimization problems"
    - "constant factor approximation for ordered k median"
    - "interpolating between k median and k center approximation algorithms for ordered k median"
    - "better guarantees for k means and euclidean k median by primal dual algorithms"

Connected through hyperedge HE-2 (induced by source paper "approximation algorithms for minimum norm and ordered optimization problems"):
  with members:
    - "constant factor approximation for ordered k median"
    - "approximate near neighbors for general symmetric norms"
    - "better guarantees for k means and euclidean k median by primal dual algorithms"
    - "streaming symmetric norms via measure concentration"
    - "an improved approximation for k median and positive correlation in budgeted optimization"
    - "approximating k median via pseudo approximation"
    - "santa claus schedules jobs on unrelated machines"
    - "simpler analyses of local search algorithms for facility location"

Connected through hyperedge HE-3 (induced by source paper "scheduling to minimize total weighted completion time via time indexed linear programming relaxations"):
  with members:
    - "better unrelated machine scheduling for weighted completion time via random offsets from non uniform distributions"
    - "a 2 542 approximation for precedence constrained single machine scheduling with release dates and total weighted completion time objective"
    - "lift and round to improve weighted completion time on unrelated machines"
    - "a 1 epsilon approximation for makespan scheduling with precedence constraints using lp hierarchies"
    - "towards tight lower bounds for scheduling problems"
    - "santa claus schedules jobs on unrelated machines"
    - "the geometry of scheduling"

Connected through hyperedge HE-4 (induced by source paper "a quasi polynomial approximation for the restricted assignment problem"):
  with members:
    - "lazy local search meets machine scheduling"
    - "on 1 epsilon restricted assignment makespan minimization"
    - "combinatorial algorithm for restricted max min fair allocation"
    - "quasi polynomial local search for restricted max min fair allocation"
    - "santa claus schedules jobs on unrelated machines"

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)