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: "paths beyond local search a nearly tight bound for randomized fixed point computation"
  Abstract: In 1983, Aldous proved that randomization can speedup local search. For example, it reduces the query complexity of local search over [1:n]^d from Theta (n^{d-1}) to O (d^{1/2}n^{d/2}). It remains open whether randomization helps fixed-point computation. Inspired by this open problem and recent advances on equilibrium computation, we have been fascinated by the following question: #R##N#Is a fixed-point or an equilibrium fundamentally harder to find than a local optimum? In this paper, we give a nearly-tight bound of Omega(n)^{d-1} on the randomized query complexity for computing a fixed point of a discrete Brouwer function over [1:n]^d. Since the randomized query complexity of global optimization over [1:n]^d is Theta (n^{d}), the randomized query model over [1:n]^d strictly separates these three important search problems: Global optimization is harder than fixed-point computation, and fixed-point computation is harder than local search. Our result indeed demonstrates that randomization does not help much in fixed-point computation in the query model; the deterministic complexity of this problem is Theta (n^{d-1}).

Connected through hyperedge HE-1 (induced by source paper "query complexity of approximate nash equilibria"):
  with members:
    - "the query complexity of correlated equilibria"
    - "inapproximability of nash equilibrium"
    - "computational complexity of approximate nash equilibrium in large games"
    - "finding approximate nash equilibria of bimatrix games via payoff queries"
    - "learning equilibria of games via payoff queries"
    - "approximate nash equilibria via sampling"
    - "query complexity of correlated equilibrium"
    - "weak calibration is computationally hard"

Connected through hyperedge HE-2 (induced by source paper "the complexity of non monotone markets"):
  with members:
    - "leontief exchange markets can solve multivariate polynomial equations yielding fixp and etr hardness"
    - "inapproximability of nash equilibrium"
    - "a complexity view of markets with social influence"
    - "settling the complexity of arrow debreu equilibria in markets with additively separable utilities"
    - "spending is not easier than trading on the computational equivalence of fisher and arrow debreu equilibria"
    - "settling the complexity of computing two player nash equilibria"
    - "on the approximation and smoothed complexity of leontief market equilibria"

Connected through hyperedge HE-3 (induced by source paper "settling the complexity of computing two player nash equilibria"):
  with members:
    - "graphical models for game theory"
    - "preference games and personalized equilibria with applications to fractional bgp"
    - "bounded budget connection bbc games or how to make friends and influence people on a budget"
    - "on the approximation and smoothed complexity of leontief market equilibria"
    - "games of fixed rank a hierarchy of bimatrix games"
    - "complexity results about nash equilibria"
    - "smoothed analysis of algorithms why the simplex algorithm usually takes polynomial time"

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)