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: "constraint satisfaction parameterized by solution size"
  Abstract: In the constraint satisfaction problem (CSP) corresponding to a constraint language (i.e., a set of relations) $\Gamma$, the goal is to find an assignment of values to variables so that a given set of constraints specified by relations from $\Gamma$ is satisfied. The complexity of this problem has received substantial amount of attention in the past decade. In this paper we study the fixed-parameter tractability of constraint satisfaction problems parameterized by the size of the solution in the following sense: one of the possible values, say 0, is "free," and the number of variables allowed to take other, "expensive," values is restricted. A size constraint requires that exactly $k$ variables take nonzero values. We also study a more refined version of this restriction: a global cardinality constraint prescribes how many variables have to be assigned each particular value. We study the parameterized complexity of these types of CSPs where the parameter is the required number $k$ of nonzero variables. As special cases, we can obtain natural and well-studied parameterized problems such as Independent Set, Vertex Cover, d-Hitting Set, Biclique, etc. #R##N#In the case of constraint languages closed under substitution of constants, we give a complete characterization of the fixed-parameter tractable cases of CSPs with size constraints, and we show that all the remaining problems are W[1]-hard. For CSPs with cardinality constraints, we obtain a similar classification, but for some of the problems we are only able to show that they are Biclique-hard. The exact parameterized complexity of the Biclique problem is a notorious open problem, although it is believed to be W[1]-hard.

Connected through hyperedge HE-1 (induced by source paper "uniform csp parameterized by solution size is in w 1"):
  with members:
    - "parameterized complexity of csp for infinite constraint languages"
    - "a polynomial turing kernel for weighted independent set in bull free graphs"
    - "improved fpt algorithms for weighted independent set in bull free graphs"
    - "losing weight by gaining edges"

Connected through hyperedge HE-2 (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-3 (induced by source paper "fixed parameter approximability of boolean mincsps"):
  with members:
    - "completely inapproximable monotone and antimonotone parameterized problems"
    - "fixed parameter and approximation algorithms a new look"
    - "the complexity of weighted and unweighted csp"
    - "the complexity of global cardinality constraints"

Connected through hyperedge HE-4 (induced by source paper "the parameterized complexity of k biclique"):
  with members:
    - "the constant inapproximability of the parameterized dominating set problem"

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)