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: "a complexity dichotomy for hitting connected minors on bounded treewidth graphs the chair and the banner draw the boundary"
  Abstract: For a fixed connected graph $H$, the $\{H\}$-M-DELETION problem asks, given a graph $G$, for the minimum number of vertices that intersect all minor models of $H$ in $G.$ It is known that this problem can be solved in time $f(tw)\cdot n^{O(1)}$, where $tw$ is the treewidth of $G.$ We determine the asymptotically optimal function $f(tw),$ for each possible choice of $H.$ Namely, we prove that, under the ETH, $f(tw) =2^{\Theta(tw)}$ if $H$ is a contraction of the chair or the banner, and $f(tw)=2^{\Theta( tw \cdot \log tw)}$ otherwise. Prior to this work, such a complete characterization was only known when $H$ is a planar graph with at most five vertices. For the upper bounds, we present an algorithm in time $2^{\Theta( tw\cdot \log tw)} \cdot n^{O(1)}$ for the more general problem where all minor models of connected graphs in a finite family ${\mathcal F}$ need to be hit. We combine several ingredients such as the machinery of boundaried graphs in dynamic programming via representatives, the Flat Wall Theorem, Bidimensionality, the irrelevant vertex technique, treewidth modulators, and protrusion replacement. In particular, this algorithm vastly generalizes a result of Jansen et al. [SODA 2014] for the particular case ${\mathcal F}=\{K_5,K_{3,3}\}.$ For the lower bounds, our reductions are based on a generic construction building on the one given by the authors in [IPEC 2018], which uses the framework introduced by Lokshtanov et al. [SODA 2011] to obtain superexponential lower bounds.

Connected through hyperedge HE-1 (induced by source paper "subexponential parameterized algorithms and kernelization on almost chordal graphs"):
  with members:
    - "feedback vertex set inspired kernel for chordal vertex deletion"
    - "approximation and kernelization for chordal vertex deletion"
    - "polynomial kernels for weighted problems"
    - "linear recognition of almost interval graphs"
    - "large induced subgraphs via triangulations and cmso"
    - "data reduction for graph coloring problems"
    - "interval deletion is fixed parameter tractable"
    - "kernelization lower bounds by cross composition"

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)