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: "scheduling to minimize total weighted completion time via time indexed linear programming relaxations"
  Abstract: We study approximation algorithms for scheduling problems with the objective of minimizing total weighted completion time, under identical and related machine models with job precedence constraints. We give algorithms that improve upon many previous 15 to 20-year-old state-of-art results. A major theme in these results is the use of time-indexed linear programming relaxations. These are natural relaxations for their respective problems, but surprisingly are not studied in the literature. #R##N#We also consider the scheduling problem of minimizing total weighted completion time on unrelated machines. The recent breakthrough result of [Bansal-Srinivasan-Svensson, STOC 2016] gave a $(1.5-c)$-approximation for the problem, based on some lift-and-project SDP relaxation. Our main result is that a $(1.5 - c)$-approximation can also be achieved using a natural and considerably simpler time-indexed LP relaxation for the problem. We hope this relaxation can provide new insights into the problem.

Connected through hyperedge HE-1 (induced by source paper "weighted completion time minimization for unrelated machines via iterative fair contention resolution"):
  with members:
    - "unrelated machine scheduling of jobs with uniform smith ratios"
    - "better unrelated machine scheduling for weighted completion time via random offsets from non uniform distributions"
    - "lift and round to improve weighted completion time on unrelated machines"
    - "minimizing flow time on unrelated machines"
    - "santa claus schedules jobs on unrelated machines"
    - "on allocating goods to maximize fairness"

Connected through hyperedge HE-2 (induced by source paper "a note on the asymptotic optimality of work conserving disciplines in completion time minimization"):
  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"

Connected through hyperedge HE-3 (induced by source paper "non clairvoyant precedence constrained scheduling"):
  with members:
    - "flow time optimization for concurrent open shop and precedence constrained scheduling models"
    - "selfishmigrate a scalable algorithm for non clairvoyantly scheduling heterogeneous processors"

Connected through hyperedge HE-4 (induced by source paper "flow time optimization for concurrent open shop and precedence constrained scheduling models"):
  with members:
    - "an improved bound for minimizing the total weighted completion time of coflows in datacenters"
    - "almost polynomial ratio eth hardness of approximating densest k subgraph"
    - "a 1 epsilon approximation for makespan scheduling with precedence constraints using lp hierarchies"
    - "competitive algorithms from competitive equilibria non clairvoyant scheduling under polyhedral constraints"
    - "selfishmigrate a scalable algorithm for non clairvoyantly scheduling heterogeneous processors"
    - "the geometry of scheduling"

Connected through hyperedge HE-5 (induced by source paper "stochastic online scheduling on unrelated machines"):
  with members:
    - "better unrelated machine scheduling for weighted completion time via random offsets from non uniform distributions"
    - "lift and round to improve weighted completion time on unrelated machines"
    - "selfishmigrate a scalable algorithm for non clairvoyantly scheduling heterogeneous processors"
    - "inner product spaces for minsum coordination mechanisms"

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)