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: "efficient coordination mechanisms for unrelated machine scheduling"
  Abstract: We present new coordination mechanisms for scheduling selfish jobs on $m$ unrelated machines. A coordination mechanism aims to mitigate the impact of selfishness of jobs on the efficiency of schedules by defining a local scheduling policy on each machine. The scheduling policies induce a game among the jobs and each job prefers to be scheduled on a machine so that its completion time is minimum given the assignments of the other jobs. We consider the maximum completion time among all jobs as the measure of the efficiency of schedules. The approximation ratio of a coordination mechanism quantifies the efficiency of pure Nash equilibria (price of anarchy) of the induced game. #R##N#Our mechanisms are deterministic, local, and preemptive. Our first coordination mechanism has approximation ratio $\Theta(\log m)$ and guarantees that the induced game has pure Nash equilibria. This result improves a bound of $O(\log^2 m)$ due to Azar, Jain, and Mirrokni and uses a global ordering of the jobs according to their distinct IDs. Our second mechanism handles anonymous jobs and has approximation ratio $O(\frac{\log m}{\log \log m})$ although the game induced is not a potential game and, hence, the existence of pure Nash equilibria is not guaranteed by potential function arguments. However, it provides evidence that the known lower bounds for non-preemptive coordination mechanisms could be beaten using preemptive scheduling policies. Our third coordination mechanism also handles anonymous jobs and has a nice cost-revealing potential function. We use this potential function in order to prove the existence of equilibria and to upper-bound the price of anarchy of the induced game by $O(\log^2m)$. Our third coordination mechanism is the first that handles anonymous jobs and simultaneously guarantees that the induced game is a potential game and has bounded price of anarchy.

Connected through hyperedge HE-1 (induced by source paper "on the price of anarchy of cost sharing in real time scheduling systems"):
  with members:
    - "sharing non anonymous costs of multiple resources optimally"
    - "potential games are necessary to ensure pure nash equilibria in cost sharing games"
    - "a model for minimizing active processor time"

Connected through hyperedge HE-2 (induced by source paper "an almost ideal coordination mechanism for unrelated machine scheduling"):
  with members:
    - "smooth inequalities and equilibrium inefficiency in scheduling games"

Connected through hyperedge HE-3 (induced by source paper "sequential solutions in machine scheduling games"):
  with members:
    - "an almost ideal coordination mechanism for unrelated machine scheduling"

Connected through hyperedge HE-4 (induced by source paper "designing networks with good equilibria under uncertainty"):
  with members:
    - "online network design algorithms via hierarchical decompositions"
    - "potential games are necessary to ensure pure nash equilibria in cost sharing games"
    - "improving the price of anarchy for selfish routing via coordination mechanisms"
    - "inner product spaces for minsum coordination mechanisms"
    - "an o lognloglogn upper bound on the price of stability for undirected shapley network design games"

Connected through hyperedge HE-5 (induced by source paper "improving the price of anarchy for selfish routing via coordination mechanisms"):
  with members:
    - "inner product spaces for minsum coordination mechanisms"

Connected through hyperedge HE-6 (induced by source paper "smooth inequalities and equilibrium inefficiency in scheduling games"):
  with members:
    - "inner product spaces for minsum coordination mechanisms"

Connected through hyperedge HE-7 (induced by source paper "approximate pure nash equilibria in weighted congestion games existence efficient computation and structure"):
  with members:
    - "efficient computation of approximate pure nash equilibria in congestion games"
    - "dynamics in near potential games"
    - "computing equilibria in anonymous games"
    - "near rationality and competitive equilibria in networked systems"

Connected through hyperedge HE-8 (induced by source paper "enforcing efficient equilibria in network design games via subsidies"):
  with members:
    - "improving the price of anarchy for selfish routing via coordination mechanisms"
    - "an o lognloglogn upper bound on the price of stability for undirected shapley network design games"
    - "the cost of stability in coalitional games"

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.GT(Computer Science and Game Theory)