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: "finding approximate nash equilibria of bimatrix games via payoff queries"
  Abstract: We study the deterministic and randomized query complexity of finding approximate equilibria in bimatrix games. We show that the deterministic query complexity of finding an $\epsilon$-Nash equilibrium when $\epsilon < \frac{1}{2}$ is $\Omega(k^2)$, even in zero-one constant-sum games. In combination with previous results \cite{FGGS13}, this provides a complete characterization of the deterministic query complexity of approximate Nash equilibria. We also study randomized querying algorithms. We give a randomized algorithm for finding a $(\frac{3 - \sqrt{5}}{2} + \epsilon)$-Nash equilibrium using $O(\frac{k \cdot \log k}{\epsilon^2})$ payoff queries, which shows that the $\frac{1}{2}$ barrier for deterministic algorithms can be broken by randomization. For well-supported Nash equilibria (WSNE), we first give a randomized algorithm for finding an $\epsilon$-WSNE of a zero-sum bimatrix game using $O(\frac{k \cdot \log k}{\epsilon^4})$ payoff queries, and we then use this to obtain a randomized algorithm for finding a $(\frac{2}{3} + \epsilon)$-WSNE in a general bimatrix game using $O(\frac{k \cdot \log k}{\epsilon^4})$ payoff queries. Finally, we initiate the study of lower bounds against randomized algorithms in the context of bimatrix games, by showing that randomized algorithms require $\Omega(k^2)$ payoff queries in order to find a $\frac{1}{6k}$-Nash equilibrium, even in zero-one constant-sum games. In particular, this rules out query-efficient randomized algorithms for finding exact Nash equilibria.

Connected through hyperedge HE-1 (induced by source paper "distributed methods for computing approximate equilibria"):
  with members:
    - "settling the complexity of computing approximate two player nash equilibria"
    - "communication complexity of approximate nash equilibria"
    - "an empirical study of finding approximate equilibria in bimatrix games"
    - "approximate well supported nash equilibria in symmetric bimatrix games"
    - "learning equilibria of games via payoff queries"
    - "on the communication complexity of approximate nash equilibria"
    - "approximate well supported nash equilibria below two thirds"
    - "settling the complexity of computing two player nash equilibria"

Connected through hyperedge HE-2 (induced by source paper "near optimal communication lower bounds for approximate nash equilibria"):
  with members:
    - "distributed methods for computing approximate equilibria"
    - "the communication complexity of local search"
    - "complexity theory game theory and economics"
    - "communication complexity of correlated equilibrium in two player games"
    - "query to communication lifting for bpp"
    - "the query complexity of correlated equilibria"
    - "settling the complexity of computing approximate two player nash equilibria"
    - "communication complexity of approximate nash equilibria"

Connected through hyperedge HE-3 (induced by source paper "well supported versus approximate nash equilibria query complexity of large games"):
  with members:
    - "the query complexity of correlated equilibria"
    - "on the structure covering and learning of poisson multinomial distributions"
    - "can almost everybody be almost happy pcp for ppad and the inapproximability of nash"
    - "on the complexity of nash equilibria in anonymous games"
    - "inapproximability of nash equilibrium"
    - "query complexity of approximate equilibria in anonymous games"
    - "constant rank bimatrix games are ppad hard"
    - "learning equilibria of games via payoff queries"

Connected through hyperedge HE-4 (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-5 (induced by source paper "learning equilibria of games via payoff queries"):
  with members:
    - "the query complexity of correlated equilibria"
    - "graphical models for game theory"
    - "on the communication complexity of approximate nash equilibria"
    - "query complexity of approximate nash equilibria"
    - "query complexity of correlated equilibrium"
    - "approximate well supported nash equilibria below two thirds"
    - "on the complexity of trial and error"
    - "on oblivious ptas s for nash equilibrium"

Connected through hyperedge HE-6 (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"
    - "learning equilibria of games via payoff queries"
    - "approximate nash equilibria via sampling"
    - "query complexity of correlated equilibrium"
    - "weak calibration is computationally hard"
    - "polynomial time computation of exact correlated equilibrium in compact games"

Connected through hyperedge HE-7 (induced by source paper "query complexity of correlated equilibrium"):
  with members:
    - "the query complexity of correlated equilibria"
    - "learning equilibria of games via payoff queries"
    - "query complexity of approximate nash equilibria"
    - "polynomial time computation of exact correlated equilibrium in compact games"
    - "settling the complexity of computing two player nash equilibria"

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)