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 multivariate framework for weighted fpt algorithms"
  Abstract: We introduce a novel multivariate approach for solving weighted parameterized problems. In our model, given an instance of size $n$ of a minimization (maximization) problem, and a parameter $W \geq 1$, we seek a solution of weight at most (or at least) $W$. We use our general framework to obtain efficient algorithms for such fundamental graph problems as Vertex Cover, 3-Hitting Set, Edge Dominating Set and Max Internal Out-Branching. The best known algorithms for these problems admit running times of the form $c^W n^{O(1)}$, for some constant $c>1$. We improve these running times to $c^s n^{O(1)}$, where $s\leq W$ is the minimum size of a solution of weight at most (at least) $W$. If no such solution exists, $s=\min\{W,m\}$, where $m$ is the maximum size of a solution. Clearly, $s$ can be substantially smaller than $W$. In particular, the running times of our algorithms are (almost) the same as the best known $O^*$ running times for the unweighted variants. Thus, we solve the weighted versions of #R##N#* Vertex Cover in $1.381^s n^{O(1)}$ time and $n^{O(1)}$ space. #R##N#* 3-Hitting Set in $2.168^s n^{O(1)}$ time and $n^{O(1)}$ space. #R##N#* Edge Dominating Set in $2.315^s n^{O(1)}$ time and $n^{O(1)}$ space. #R##N#* Max Internal Out-Branching in $6.855^s n^{O(1)}$ time and space. #R##N#We further show that Weighted Vertex Cover and Weighted Edge Dominating Set admit fast algorithms whose running times are of the form $c^t n^{O(1)}$, where $t \leq s$ is the minimum size of a solution.

Connected through hyperedge HE-1 (induced by source paper "exact algorithms via monotone local search"):
  with members:
    - "exact algorithms for maximum independent set"
    - "faster algorithms to enumerate hypergraph transversals"
    - "a faster fpt algorithm and a smaller kernel for block graph vertex deletion"
    - "faster exact and parameterized algorithm for feedback vertex set in tournaments"
    - "on feedback vertex set new measure and new structures"
    - "an fpt algorithm and a polynomial kernel for linear rankwidth 1 vertex deletion"
    - "unit interval editing is fixed parameter tractable"
    - "linear recognition of almost interval graphs"

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)