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: "preprocessing of min ones problems a dichotomy"
  Abstract: A parameterized problem consists of a classical problem and an additional component, the so-called parameter. This point of view allows a formal definition of preprocessing: Given a parameterized instance (I,k), a polynomial kernelization computes an equivalent instance (I',k') of size and parameter bounded by a polynomial in k. We give a complete classification of Min Ones Constraint Satisfaction problems, i.e., Min Ones SAT(\Gamma), with respect to admitting or not admitting a polynomial kernelization (unless NP \subseteq coNP/poly). For this we introduce the notion of mergeability. If all relations of the constraint language \Gamma are mergeable, then a new variant of sunflower kernelization applies, based on non-zero-closed cores. We obtain a kernel with O(k^{d+1}) variables and polynomial total size, where d is the maximum arity of a constraint in \Gamma, comparing nicely with the bound of O(k^{d-1}) vertices for the less general and arguably simpler d-Hitting Set problem. Otherwise, any relation in \Gamma that is not mergeable permits us to construct a log-cost selection formula, i.e., an n-ary selection formula with O(log n) true local variables. From this we can construct our lower bound using recent results by Bodlaender et al. as well as Fortnow and Santhanam, proving that there is no polynomial kernelization, unless NP \subseteq coNP/poly and the polynomial hierarchy collapses to the third level.

Connected through hyperedge HE-1 (induced by source paper "optimal polynomial time compression for boolean max csp"):
  with members:
    - "a dichotomy theorem for nonuniform csps"
    - "kernelization of constraint satisfaction problems a study through universal algebra"
    - "the proof of csp dichotomy conjecture"
    - "tight hardness for shortest cycles and paths in sparse graphs"
    - "sparsification upper and lower bounds for graph problems and not all equal sat"
    - "complexity of counting csp with complex weights"
    - "the approximability of max csp with fixed value constraints"

Connected through hyperedge HE-2 (induced by source paper "kernelization of constraint satisfaction problems a study through universal algebra"):
  with members:
    - "on the hardness of losing weight"
    - "a dichotomy theorem for nonuniform csps"
    - "the proof of csp dichotomy conjecture"
    - "optimal sparsification for some binary csps using low degree polynomials"
    - "sparsification upper and lower bounds for graph problems and not all equal sat"
    - "an effective dichotomy for the counting constraint satisfaction problem"

Connected through hyperedge HE-3 (induced by source paper "optimal sparsification for some binary csps using low degree polynomials"):
  with members:
    - "optimal data reduction for graph coloring using low degree polynomials"
    - "best case and worst case sparsifiability of boolean csps"
    - "kernelization of constraint satisfaction problems a study through universal algebra"
    - "complexity and approximability of parameterized max csps"
    - "sparsification upper and lower bounds for graph problems and not all equal sat"
    - "nonclassical polynomials as a barrier to polynomial lower bounds"
    - "on sparsification for computing treewidth"
    - "kernelization lower bounds by cross composition"

Connected through hyperedge HE-4 (induced by source paper "kernelization of packing problems"):
  with members:
    - "bidimensionality and kernels"
    - "preprocessing for treewidth a combinatorial analysis through kernelization"
    - "cross composition a new technique for kernelization lower bounds"
    - "kernel s for problems with no kernel on out trees with many leaves"

Connected through hyperedge HE-5 (induced by source paper "constraint satisfaction parameterized by solution size"):
  with members:
    - "on the hardness of losing weight"
    - "kernels for global constraints"
    - "the complexity of global cardinality constraints"

Connected through hyperedge HE-6 (induced by source paper "hierarchies of inefficient kernelizability"):
  with members:
    - "data reduction for graph coloring problems"
    - "kernel bounds for path and cycle problems"
    - "on polynomial kernels for structural parameterizations of odd cycle transversal"
    - "cross composition a new technique for kernelization lower bounds"
    - "solving max r sat above a tight lower bound"
    - "polynomial time data reduction for dominating set"

Connected through hyperedge HE-7 (induced by source paper "co nondeterminism in compositions a kernelization lower bound for a ramsey type problem"):
  with members:
    - "kernelization of packing problems"
    - "cross composition a new technique for kernelization lower bounds"
    - "kernel s for problems with no kernel on out trees with many leaves"

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)