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: "optimal algorithms for hitting topological minors on graphs of bounded treewidth"
  Abstract: For a fixed collection of graphs ${\cal F}$, the ${\cal F}$-M-DELETION problem consists in, given a graph $G$ and an integer $k$, decide whether there exists $S \subseteq V(G)$ with $|S| \leq k$ such that $G \setminus S$ does not contain any of the graphs in ${\cal F}$ as a minor. We are interested in the parameterized complexity of ${\cal F}$-M-DELETION when the parameter is the treewidth of $G$, denoted by $tw$. Our objective is to determine, for a fixed ${\cal F}$, the smallest function $f_{{\cal F}}$ such that ${\cal F}$-M-DELETION can be solved in time $f_{{\cal F}}(tw) \cdot n^{O(1)}$ on $n$-vertex graphs. Using and enhancing the machinery of boundaried graphs and small sets of representatives introduced by Bodlaender et al. [J ACM, 2016], we prove that when all the graphs in ${\cal F}$ are connected and at least one of them is planar, then $f_{{\cal F}}(w) = 2^{O (w \cdot\log w)}$. When ${\cal F}$ is a singleton containing a clique, a cycle, or a path on $i$ vertices, we prove the following asymptotically tight bounds: #R##N#$\bullet$ $f_{\{K_4\}}(w) = 2^{\Theta (w \cdot \log w)}$. #R##N#$\bullet$ $f_{\{C_i\}}(w) = 2^{\Theta (w)}$ for every $i \leq 4$, and $f_{\{C_i\}}(w) = 2^{\Theta (w \cdot\log w)}$ for every $i \geq 5$. #R##N#$\bullet$ $f_{\{P_i\}}(w) = 2^{\Theta (w)}$ for every $i \leq 4$, and $f_{\{P_i\}}(w) = 2^{\Theta (w \cdot \log w)}$ for every $i \geq 6$. #R##N#The lower bounds hold unless the Exponential Time Hypothesis fails, and the superexponential ones are inspired by a reduction of Marcin Pilipczuk [Discrete Appl Math, 2016]. The single-exponential algorithms use, in particular, the rank-based approach introduced by Bodlaender et al. [Inform Comput, 2015]. We also consider the version of the problem where the graphs in ${\cal F}$ are forbidden as topological minors, and prove that essentially the same set of results holds.

Connected through hyperedge HE-1 (induced by source paper "a complexity dichotomy for hitting connected minors on bounded treewidth graphs the chair and the banner draw the boundary"):
  with members:
    - "composing dynamic programming tree decomposition based algorithms"
    - "hitting topological minor models in planar graphs is fixed parameter tractable"
    - "slightly superexponential parameterized problems"
    - "deleting vertices to graphs of bounded genus"
    - "generalized feedback vertex set problems on bounded treewidth graphs chordality is the key to single exponential parameterized algorithms"
    - "hitting minors on bounded treewidth graphs"
    - "explicit linear kernels for packing problems"
    - "bidimensionality and kernels"

Connected through hyperedge HE-2 (induced by source paper "decomposition of map graphs with applications"):
  with members:
    - "finding hitting and packing cycles in subexponential time on unit disk graphs"
    - "solving connectivity problems parameterized by treewidth in single exponential time"
    - "bidimensionality and geometric graphs"

Connected through hyperedge HE-3 (induced by source paper "generalized feedback vertex set problems on bounded treewidth graphs chordality is the key to single exponential parameterized algorithms"):
  with members:
    - "slightly superexponential parameterized problems"
    - "parameterized vertex deletion problems for hereditary graph classes with a block property"
    - "deleting edges to restrict the size of an epidemic a new application for treewidth"
    - "on the computational complexity of vertex integrity and component order connectivity"
    - "solving connectivity problems parameterized by treewidth in single exponential time"
    - "known algorithms on graphs of bounded treewidth are probably optimal"

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)