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 "lagrangian duality based algorithms in online scheduling"):
  Abstract: We consider Lagrangian duality based approaches to design and analyze algorithms for online energy-efficient scheduling. First, we present a primal-dual framework. Our approach makes use of the Lagrangian weak duality and convexity to derive dual programs for problems which could be formulated as convex assignment problems. The duals have intuitive structures as the ones in linear programming. The constraints of the duals explicitly indicate the online decisions and naturally lead to competitive algorithms. Second, we use a dual-fitting approach, which also based on the weak duality, to study problems which are unlikely to admit convex relaxations. Through the analysis, we show an interesting feature in which primal-dual gives idea for designing algorithms while the analysis is done by dual-fitting. #R##N#We illustrate the advantages and the flexibility of the approaches through problems in different setting: from single machine to unrelated machine environments, from typical competitive analysis to the one with resource augmentation, from convex relaxations to non-convex relaxations.

Includes members:
  Member "competitive algorithms from competitive equilibria non clairvoyant scheduling under polyhedral constraints":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "dynamic weighted fairness with minimal disruptions")
  Member "selfishmigrate a scalable algorithm for non clairvoyantly scheduling heterogeneous processors":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a unifying optimal control framework for online job scheduling with general cost functions")
  Member "speed scaling with power down scheduling for agreeable deadlines":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a fully polynomial time approximation scheme for speed scaling with sleep state")
  Member "profitable scheduling on multiple speed scalable processors":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "throughput maximization in multiprocessor speed scaling")
  Member "online primal dual for non linear optimization with applications to speed scaling":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "station assignment with reallocation")

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)