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: "tight running time lower bounds for vertex deletion problems"
  Abstract: For a graph class $\Pi$, the $\Pi$-Vertex Deletion problem has as input an undirected graph $G=(V,E)$ and an integer $k$ and asks whether there is a set of at most $k$ vertices that can be deleted from $G$ such that the resulting graph is a member of $\Pi$. By a classic result of Lewis and Yannakakis [J. Comput. Syst. Sci. '80], $\Pi$-Vertex Deletion is NP-hard for all hereditary properties $\Pi$. We adapt the original NP-hardness construction to show that under the Exponential Time Hypothesis (ETH) tight complexity results can be obtained. We show that $\Pi$-Vertex Deletion does not admit a $2^{o(n)}$-time algorithm where $n$ is the number of vertices in $G$. We also obtain a dichotomy for running time bounds that include the number $m$ of edges in the input graph: On the one hand, if $\Pi$ contains all independent sets, then there is no $2^{o(n+m)}$-time algorithm for $\Pi$-Vertex Deletion. On the other hand, if there is a fixed independent set that is not contained in $\Pi$ and containment in $\Pi$ can determined in $2^{O(n)}$ time or $2^{o(m)}$ time, then $\Pi$-Vertex Deletion can be solved in $2^{O(\sqrt{m})}+O(n)$ or $2^{o({m})}+O(n)$ time, respectively. We also consider restrictions on the domain of the input graph $G$. For example, we obtain that $\Pi$-Vertex Deletion cannot be solved in $2^{o(\sqrt{n})}$ time if $G$ is planar and $\Pi$ is hereditary and contains and excludes infinitely many planar graphs. Finally, we provide similar results for the problem variant where the deleted vertex set has to induce a connected graph.

Connected through hyperedge HE-1 (induced by source paper "subexponential time algorithms for finding large induced sparse subgraphs"):
  with members:
    - "deleting vertices to graphs of bounded genus"
    - "polynomial time algorithm for maximum weight independent set on p_6 free graphs"
    - "exact algorithms via monotone local search"
    - "hitting forbidden subgraphs in graphs of bounded treewidth"
    - "large induced subgraphs via triangulations and cmso"
    - "largest chordal and interval subgraphs faster than 2 n"
    - "finding a maximum induced degenerate subgraph faster than 2 n"
    - "problems parameterized by treewidth tractable in single exponential time a logical approach"

Connected through hyperedge HE-2 (induced by source paper "destroying bicolored p_3 s by deleting few edges"):
  with members:
    - "on the relation of strong triadic closure and cluster deletion"
    - "fast quasi threshold editing"
    - "phylogenomics with paralogs"

Connected through hyperedge HE-3 (induced by source paper "structural rounding approximation algorithms for graphs near an algorithmically tractable class"):
  with members:
    - "approximate generalized matching f factors and f edge covers"
    - "optimal dynamic program for r domination problems over tree decompositions"
    - "inapproximability of h transversal packing"
    - "polynomial bounds for the grid minor theorem"
    - "approximation algorithms for maximum independent set of pseudo disks"
    - "obtaining a planar graph by vertex deletion"

Connected through hyperedge HE-4 (induced by source paper "simultaneous feedback vertex set a parameterized perspective"):
  with members:
    - "a note on finding dual feedback vertex set"
    - "faster deterministic feedback vertex set"
    - "interval deletion is fixed parameter tractable"
    - "linear kernels and single exponential algorithms via protrusion decompositions"
    - "faster parameterized algorithms using linear programming"
    - "representative sets and irrelevant vertices new tools for kernelization"
    - "solving connectivity problems parameterized by treewidth in single exponential time"
    - "obtaining a planar graph by vertex deletion"

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)