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 experimental analysis of lemke howson algorithm"
  Abstract: We present an experimental investigation of the performance of the Lemke-Howson algorithm, which is the most widely used algorithm for the computation of a Nash equilibrium for bimatrix games. Lemke-Howson algorithm is based upon a simple pivoting strategy, which corresponds to following a path whose endpoint is a Nash equilibrium. We analyze both the basic Lemke-Howson algorithm and a heuristic modification of it, which we designed to cope with the effects of a 'bad' initial choice of the pivot. Our experimental findings show that, on uniformly random games, the heuristics achieves a linear running time, while the basic Lemke-Howson algorithm runs in time roughly proportional to a polynomial of degree seven. To conduct the experiments, we have developed our own implementation of Lemke-Howson algorithm, which turns out to be significantly faster than state-of-the-art software. This allowed us to run the algorithm on a much larger set of data, and on instances of much larger size, compared with previous work.

Connected through hyperedge HE-1 (induced by source paper "smoothed efficient algorithms and reductions for network coordination games"):
  with members:
    - "improving the smoothed complexity of flip for max cut problems"
    - "near optimal communication lower bounds for approximate nash equilibria"
    - "efficient local search in coordination games on graphs"
    - "settling the complexity of computing approximate two player nash equilibria"
    - "communication complexity of approximate nash equilibria"
    - "the price of anarchy in auctions"
    - "inapproximability of nash equilibrium"
    - "constant rank bimatrix games are ppad hard"

Connected through hyperedge HE-2 (induced by source paper "nash equilibrium in smoothed polynomial time for network coordination games"):
  with members:
    - "near optimal communication lower bounds for approximate nash equilibria"
    - "local max cut in smoothed polynomial time"
    - "an empirical study on computing equilibria in polymatrix games"
    - "communication complexity of approximate nash equilibria"
    - "inapproximability of nash equilibrium"
    - "constant rank bimatrix games are ppad hard"
    - "query complexity of approximate nash equilibria"
    - "bilinear games polynomial time algorithms for rank based subclasses"

Connected through hyperedge HE-3 (induced by source paper "an empirical study of finding approximate equilibria in bimatrix games"):
  with members:
    - "unit vector games"
    - "ranking games that have competitiveness based strategies"
    - "polylogarithmic supports are required for approximate well supported nash equilibria below 2 3"
    - "combining local search techniques and path following for bimatrix games"
    - "approximate well supported nash equilibria below two thirds"
    - "the complexity of the homotopy method equilibrium selection and lemke howson solutions"
    - "settling the complexity of computing two player nash equilibria"

Connected through hyperedge HE-4 (induced by source paper "combining local search techniques and path following for bimatrix games"):
  with members:
    - "settling the complexity of computing two player nash equilibria"
    - "computing nash equilibria approximation and smoothed complexity"

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.DS(Data Structures and Algorithms)