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: "improved bounds for the flat wall theorem"
  Abstract: The Flat Wall Theorem of Robertson and Seymour states that there is some function $f$, such that for all integers $w,t>1$, every graph $G$ containing a wall of size $f(w,t)$, must contain either (i) a $K_t$-minor; or (ii) a small subset $A\subset V(G)$ of vertices, and a flat wall of size $w$ in $G\setminus A$. Kawarabayashi, Thomas and Wollan recently showed a self-contained proof of this theorem with the following two sets of parameters: (1) $f(w,t)=\Theta(t^{24}(t^2+w))$ with $|A|=O(t^{24})$, and (2) $f(w,t)=w^{2^{\Theta(t^{24})}}$ with $|A|\leq t-5$. The latter result gives the best possible bound on $|A|$. In this paper we improve their bounds to $f(w,t)=\Theta(t(t+w))$ with $|A|\leq t-5$. For the special case where the maximum vertex degree in $G$ is bounded by $D$, we show that, if $G$ contains a wall of size $\Omega(Dt(t+w))$, then either $G$ contains a $K_t$-minor, or there is a flat wall of size $w$ in $G$. This setting naturally arises in algorithms for the Edge-Disjoint Paths problem, with $D\leq 4$. Like the proof of Kawarabayashi et al., our proof is self-contained, except for using a well-known theorem on routing pairs of disjoint paths. We also provide efficient algorithms that return either a model of the $K_t$-minor, or a vertex set $A$ and a flat wall of size $w$ in $G\setminus A$. #R##N#We complement our result for the low-degree scenario by proving an almost matching lower bound: namely, for all integers $w,t>1$, there is a graph $G$, containing a wall of size $\Omega(wt)$, such that the maximum vertex degree in $G$ is 5, and $G$ contains no flat wall of size $w$, and no $K_t$-minor.

Connected through hyperedge HE-1 (induced by source paper "hitting topological minors is fpt"):
  with members:
    - "hitting topological minor models in planar graphs is fixed parameter tractable"
    - "improved analysis of highest degree branching for feedback vertex set"
    - "losing treewidth by separating subsets"
    - "a 2 approximation algorithm for feedback vertex set in tournaments"
    - "polylogarithmic approximation for minimum planarization almost"
    - "exact algorithms for maximum independent set"
    - "bidimensionality and kernels"
    - "exact algorithms via monotone local search"

Connected through hyperedge HE-2 (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"
    - "optimal algorithms for hitting topological minors on graphs of bounded treewidth"
    - "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"

Connected through hyperedge HE-3 (induced by source paper "clique width of graph classes defined by two forbidden induced subgraphs"):
  with members:
    - "the behavior of clique width under graph operations and graph transformations"
    - "bounding the clique width of h free chordal graphs"
    - "isomorphism testing for graphs of bounded rank width"
    - "bounding the clique width of h free split graphs"
    - "bounding clique width via perfect graphs"
    - "classifying the clique width of h free bipartite graphs"
    - "a survey on the computational complexity of colouring graphs with forbidden subgraphs"
    - "towards an isomorphism dichotomy for hereditary graph classes"

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)