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: "an efficient ptas for two strategy anonymous games"
  Abstract: We present a novel polynomial time approximation scheme for two-strategy anonymous games, in which the players' utility functions, although potentially different, do not differentiate among the identities of the other players. Our algorithm computes an $eps$-approximate Nash equilibrium of an $n$-player 2-strategy anonymous game in time $poly(n) (1/eps)^{O(1/eps^2)}$, which significantly improves upon the running time $n^{O(1/eps^2)}$ required by the algorithm of Daskalakis & Papadimitriou, 2007. The improved running time is based on a new structural understanding of approximate Nash equilibria: We show that, for any $eps$, there exists an $eps$-approximate Nash equilibrium in which either only $O(1/eps^3)$ players randomize, or all players who randomize use the same mixed strategy. To show this result we employ tools from the literature on Stein's Method.

Connected through hyperedge HE-1 (induced by source paper "query complexity of approximate equilibria in anonymous games"):
  with members:
    - "playing anonymous games using simple strategies"
    - "a size free clt for poisson multinomials and its applications"
    - "the query complexity of correlated equilibria"
    - "settling the complexity of computing approximate two player nash equilibria"
    - "communication complexity of approximate nash equilibria"
    - "the fourier transform of poisson multinomial distributions and its algorithmic applications"
    - "well supported versus approximate nash equilibria query complexity of large games"
    - "optimal learning via the fourier transform for sums of independent integer random variables"

Connected through hyperedge HE-2 (induced by source paper "on the complexity of nash equilibria in anonymous games"):
  with members:
    - "inapproximability of nash equilibrium"
    - "query complexity of approximate equilibria in anonymous games"
    - "constant rank bimatrix games are ppad hard"
    - "the complexity of non monotone markets"
    - "efficient computation of approximate pure nash equilibria in congestion games"
    - "approximate pure nash equilibria in weighted congestion games existence efficient computation and structure"
    - "on oblivious ptas s for nash equilibrium"
    - "discretized multinomial distributions and nash equilibria in anonymous games"

Connected through hyperedge HE-3 (induced by source paper "ranking games that have competitiveness based strategies"):
  with members:
    - "graphical models for game theory"
    - "approximate well supported nash equilibria below two thirds"
    - "on oblivious ptas s for nash equilibrium"
    - "discretized multinomial distributions and nash equilibria in anonymous games"
    - "approximate equilibria in games with few players"
    - "settling the complexity of computing two player nash equilibria"

Connected through hyperedge HE-4 (induced by source paper "learning poisson binomial distributions"):
  with members:
    - "near optimal sample estimators for spherical gaussian mixtures"
    - "faster and sample near optimal algorithms for proper learning mixtures of gaussians"
    - "learning mixtures of structured distributions over discrete domains"
    - "on oblivious ptas s for nash equilibrium"
    - "learning k modal distributions via testing"
    - "settling the polynomial learnability of mixtures of gaussians"
    - "multiple precision zero finding methods and the complexity of elementary function evaluation"
    - "polynomial learning of distribution families"

Connected through hyperedge HE-5 (induced by source paper "on oblivious ptas s for nash equilibrium"):
  with members:
    - "discretized multinomial distributions and nash equilibria in anonymous games"
    - "computing equilibria in anonymous games"

Connected through hyperedge HE-6 (induced by source paper "learning transformed product distributions"):
  with members:
    - "on oblivious ptas s for nash equilibrium"

Connected through hyperedge HE-7 (induced by source paper "discretized multinomial distributions and nash equilibria in anonymous games"):
  with members:
    - "graphical models for game theory"
    - "on oblivious ptas s for nash equilibrium"
    - "computing equilibria in anonymous games"
    - "computing nash equilibria approximation and smoothed complexity"
    - "computing pure nash equilibria via markov random fields"
    - "games of fixed rank a hierarchy of bimatrix 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)