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: "computing nested fixpoints in quasipolynomial time"
  Abstract: It is well known that the winning region of a parity game with $n$ nodes and $k$ priorities can be computed as a $k$-nested fixpoint of a suitable function; straightforward computation of this nested fixpoint requires $n^{\lceil\frac{k}{2}\rceil+1}$ iterations of the function. The recent parity game solving algorithm by Calude et al. runs in quasipolynomial time and essentially shows how to compute the same fixpoint using only a quasipolynomial number of iterations. We show that their central idea naturally generalizes to the computation of $k$-nested fixpoints of any set-valued function; hence $k$-nested fixpoints of set functions that can be computed in quasipolynomial time can be computed in quasipolynomial time as well. While this result is of clear interest in itself, we focus in particular on applications to modal fixpoint logics beyond relational semantics. For instance, the model checking problems for the graded and the (two-valued) probabilistic $\mu$-calculus -- with numbers coded in binary -- can be solved by computing nested fixpoints of functions that differ from the function for parity game solving, but still can be computed in quasipolynomial time; our result hence implies that model checking for these $\mu$-calculi is in QP. A second implication of our result lies in satisfiability checking for generalized $\mu$-calculi, including the graded, probabilistic and alternating-time variants; in a general setting that covers all the mentioned cases, our result immediately improves the upper time bound for satisfiability checking for fixpoint formulas of size $n$ with alternation-depth $k$ from $2^{\mathcal{O}({n^2k^2\log n})}$ to $2^{\mathcal{O}({nk\log n})}$.

Connected through hyperedge HE-1 (induced by source paper "a universal attractor decomposition algorithm for parity games"):
  with members:
    - "practical synthesis of reactive systems from ltl specifications via parity games"
    - "improving the complexity of parys recursive algorithm"
    - "alternating weak automata from universal trees"
    - "parity games zielonka s algorithm in quasi polynomial time"
    - "fixpoint games on continuous lattices"
    - "quasipolynomial set based symbolic algorithms for parity games"
    - "oink an implementation and evaluation of modern parity game solvers"
    - "succinct progress measures for solving parity games"

Connected through hyperedge HE-2 (induced by source paper "the strahler number of a parity game"):
  with members:
    - "a universal attractor decomposition algorithm for parity games"
    - "parity games another view on lehtinen s algorithm"
    - "alternating weak automata from universal trees"
    - "parity games zielonka s algorithm in quasi polynomial time"
    - "universal trees grow inside separating automata quasi polynomial lower bounds for parity games"
    - "succinct progress measures for solving parity games"
    - "exponential lower bounds for policy iteration"

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)