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: "directed subset feedback vertex set is fixed parameter tractable"
  Abstract: Given a graph $G$ and an integer $k$, the Feedback Vertex Set (FVS) problem asks if there is a vertex set $T$ of size at most $k$ that hits all cycles in the graph. The fixed-parameter tractability status of FVS in directed graphs was a long-standing open problem until Chen et al. (STOC '08) showed that it is FPT by giving a $4^{k}k!n^{O(1)}$ time algorithm. In the subset versions of this problems, we are given an additional subset $S$ of vertices (resp., edges) and we want to hit all cycles passing through a vertex of $S$ (resp. an edge of $S$). Recently, the Subset Feedback Vertex Set in undirected graphs was shown to be FPT by Cygan et al. (ICALP '11) and independently by Kakimura et al. (SODA '12). We generalize the result of Chen et al. (STOC '08) by showing that Subset Feedback Vertex Set in directed graphs can be solved in time $2^{O(k^3)}n^{O(1)}$. By our result, we complete the picture for feedback vertex set problems and their subset versions in undirected and directed graphs. Besides proving the fixed-parameter tractability of Directed Subset Feedback Vertex Set, we reformulate the random sampling of important separators technique in an abstract way that can be used for a general family of transversal problems. Moreover, we modify the probability distribution used in the technique to achieve better running time; in particular, this gives an improvement from $2^{2^{O(k)}}$ to $2^{O(k^2)}$ in the parameter dependence of the Directed Multiway Cut algorithm of Chitnis et al. (SODA '12).

Connected through hyperedge HE-1 (induced by source paper "hitting long directed cycles is fixed parameter tractable"):
  with members:
    - "reducing cmso model checking to highly connected graphs"
    - "dag width and circumference of digraphs"
    - "on feedback vertex set new measure and new structures"
    - "a randomized algorithm for long directed cycle"
    - "representative sets of product families"
    - "representative families a unified tradeoff based approach"
    - "the directed grid theorem"
    - "faster deterministic feedback vertex set"

Connected through hyperedge HE-2 (induced by source paper "parameterized algorithms for generalizations of directed feedback vertex set"):
  with members:
    - "linear kernels for separating a graph into components of bounded size"
    - "a 2 ell k kernel for ell component order connectivity"
    - "dag width and circumference of digraphs"
    - "hardness of vertex deletion and project scheduling"
    - "fixed parameter tractability of directed multiway cut parameterized by the size of the cutset"

Connected through hyperedge HE-3 (induced by source paper "towards a theory of parameterized streaming algorithms"):
  with members:
    - "towards tight er bounds for the excluded grid theorem"
    - "the sparse awakens streaming algorithms for matching size estimation in sparse graphs"
    - "tight bounds for single pass streaming complexity of the set cover problem"
    - "towards tight bounds for the streaming set cover problem"
    - "polynomial bounds for the grid minor theorem"

Connected through hyperedge HE-4 (induced by source paper "subset feedback vertex set in chordal and split graphs"):
  with members:
    - "exact algorithms via monotone local search"
    - "a randomized polynomial kernel for subset feedback vertex set"
    - "half integrality lp branching and fpt algorithms"
    - "hitting forbidden minors approximation and kernelization"
    - "subset feedback vertex set is fixed parameter tractable"

Connected through hyperedge HE-5 (induced by source paper "fpt algorithms for generalized feedback vertex set problems"):
  with members:
    - "detecting feedback vertex sets of size k in o star 2 7 k time"
    - "improved analysis of highest degree branching for feedback vertex set"
    - "smaller parameters for vertex cover kernelization"
    - "on feedback vertex set new measure and new structures"
    - "subset feedback vertex set is fixed parameter tractable"

Connected through hyperedge HE-6 (induced by source paper "multi budgeted directed cuts"):
  with members:
    - "parameterized complexity and approximability of directed odd cycle transversal"
    - "linear time kernelization for feedback vertex set"
    - "a linear time parameterized algorithm for directed feedback vertex set"
    - "directed multicut is w 1 hard even for four terminal pairs"
    - "half integrality lp branching and fpt algorithms"
    - "list h coloring a graph by removing few vertices"
    - "designing fpt algorithms for cut problems using randomized contractions"
    - "representative sets and irrelevant vertices new tools for kernelization"

Connected through hyperedge HE-7 (induced by source paper "efficient algorithms for measuring the funnel likeness of dags"):
  with members:
    - "feedback vertex set in mixed graphs"
    - "kernels for feedback arc set in tournaments"

Connected through hyperedge HE-8 (induced by source paper "on directed feedback vertex set parameterized by treewidth"):
  with members:
    - "slightly superexponential parameterized problems"
    - "a linear time parameterized algorithm for directed feedback vertex set"
    - "optimal parameterized algorithms for planar facility location problems using voronoi diagrams"
    - "directed multicut is w 1 hard even for four terminal pairs"
    - "fixed parameter tractability of multicut in directed acyclic graphs"
    - "representative sets and irrelevant vertices new tools for kernelization"
    - "fixed parameter tractability of directed multiway cut parameterized by the size of the cutset"

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.DS(Data Structures and Algorithms)