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: "the complexity of the kth largest subset problem and related problems"
  Abstract: We show that the Kth largest subset problem and the Kth largest m-tuple problem are in PP and hard for PP under polynomial-time Turing reductions. Several problems from the literature were previously shown NP-hard via reductions from those two problems, and by our main result they become PP-hard as well. We also provide complementary PP-upper bounds for some of them.

Connected through hyperedge HE-1 (induced by source paper "expected window mean payoff"):
  with members:
    - "stability in graphs and games"
    - "on the complexity of heterogeneous multidimensional quantitative games"
    - "looking at mean payoff through foggy windows"
    - "trading performance for stability in markov decision processes"
    - "looking at mean payoff and total payoff through windows"

Connected through hyperedge HE-2 (induced by source paper "efficient quantile computation in markov chains via counting problems for parikh images"):
  with members:
    - "complexity of problems of commutative grammars"
    - "counting euler tours in undirected bounded treewidth graphs"
    - "unifying two views on multiple mean payoff objectives in markov decision processes"
    - "multidimensional beyond worst case and almost sure problems for mean payoff objectives"
    - "variations on the stochastic shortest path problem"
    - "the odds of staying on budget"
    - "percentile queries in multi dimensional markov decision processes"
    - "computing quantiles in markov reward models"

Connected through hyperedge HE-3 (induced by source paper "percentile queries in multi dimensional markov decision processes"):
  with members:
    - "unifying two views on multiple mean payoff objectives in markov decision processes"
    - "exact and approximate determinization of discounted sum automata"
    - "variations on the stochastic shortest path problem"
    - "the odds of staying on budget"
    - "quantitative games with interval objectives"
    - "decidability problems for actor systems"
    - "markov decision processes with multiple long run averageobjectives"
    - "to reach or not to reach efficient algorithms for total payoff games"

Connected through hyperedge HE-4 (induced by source paper "the odds of staying on budget"):
  with members:
    - "variations on the stochastic shortest path problem"
    - "percentile queries in multi dimensional markov decision processes"
    - "computing quantiles in markov reward models"
    - "meet your expectations with guarantees beyond worst case synthesis in quantitative games"
    - "approximating the termination value of one counter mdps and stochastic games"
    - "one counter markov decision processes"

Connected through hyperedge HE-5 (induced by source paper "meet your expectations with guarantees beyond worst case synthesis in quantitative games"):
  with members:
    - "variations on the stochastic shortest path problem"
    - "symblicit algorithms for optimal strategy synthesis in monotonic markov decision processes"
    - "percentile queries in multi dimensional markov decision processes"
    - "expectations or guarantees i want it all a crossroad between games and mdps"
    - "trading performance for stability in markov decision processes"
    - "looking at mean payoff and total payoff through windows"
    - "the complexity of multi mean payoff and multi energy games"
    - "strategy synthesis for multi dimensional quantitative objectives"

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.CC(Computational Complexity)