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: "multi parameter complexity analysis for constrained size graph problems using greediness for parameterization"
  Abstract: We study the parameterized complexity of a broad class of problems called "local graph partitioning problems" that includes the classical fixed cardinality problems as max k-vertex cover, k-densest subgraph, etc. By developing a technique "greediness-for-parameterization", we obtain fixed parameter algorithms with respect to a pair of parameters k, the size of the solution (but not its value) and \Delta, the maximum degree of the input graph. In particular, greediness-for-parameterization improves asymptotic running times for these problems upon random separation (that is a special case of color coding) and is more intuitive and simple. Then, we show how these results can be easily extended for getting standard-parameterization results (i.e., with parameter the value of the optimal solution) for a well known local graph partitioning problem.

Connected through hyperedge HE-1 (induced by source paper "parameterized algorithms for graph partitioning problems"):
  with members:
    - "representative sets of product families"
    - "faster computation of representative families for uniform matroids with applications"
    - "representative families a unified tradeoff based approach"
    - "deterministic parameterized algorithms for matching and packing problems"
    - "minimum bisection is fixed parameter tractable"
    - "designing fpt algorithms for cut problems using randomized contractions"

Connected through hyperedge HE-2 (induced by source paper "sparsification and subexponential approximation"):
  with members:
    - "fixed parameter and approximation algorithms a new look"
    - "independent set induced matching and pricing connections and tight subexponential time approximation hardnesses"
    - "an exponential time 2 approximation algorithm for bandwidth"
    - "exponential time approximation of hard problems"

Connected through hyperedge HE-3 (induced by source paper "parameterized exact and approximation algorithms for maximum k set cover and related satisfiability problems"):
  with members:
    - "the constant inapproximability of the parameterized dominating set problem"
    - "multiparameterizations for max k set cover and related satisfiability problems"
    - "approximating low dimensional coverage problems"

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)