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: "on feedback vertex set new measure and new structures"
  Abstract: We present a new parameterized algorithm for the feedback vertex set problem (fvs) on undirected graphs. We approach the problem by considering a variation of it, the disjoint feedback vertex set problem (disjoint-fvs), which finds a feedback vertex set of size $$k$$k that has no overlap with a given feedback vertex set $$F$$F of the graph $$G$$G. We develop an improved kernelization algorithm for disjoint-fvs and show that disjoint-fvs can be solved in polynomial time when all vertices in $$G{\setminus }F$$G\F have degrees upper bounded by three. We then propose a new branch-and-search process on disjoint-fvs, and introduce a new branch-and-search measure. The process effectively reduces a given graph to a graph on which disjoint-fvs becomes polynomial-time solvable, and the new measure more accurately evaluates the efficiency of the process. These algorithmic and combinatorial studies enable us to develop an $$O^*(3.83^k)$$OÂ?(3.83k)-time parameterized algorithm for the general fvs problem, improving all previous algorithms for the problem.

Connected through hyperedge HE-1 (induced by source paper "hitting long directed cycles is fixed parameter tractable"):
  with members:
    - "reducing cmso model checking to highly connected graphs"
    - "dag width and circumference of digraphs"
    - "a randomized algorithm for long directed cycle"
    - "representative sets of product families"
    - "representative families a unified tradeoff based approach"
    - "the directed grid theorem"
    - "faster deterministic feedback vertex set"
    - "directed subset feedback vertex set is fixed parameter tractable"

Connected through hyperedge HE-2 (induced by source paper "detecting feedback vertex sets of size k in o star 2 7 k time"):
  with members:
    - "losing treewidth by separating subsets"
    - "a naive algorithm for feedback vertex set"
    - "fine grained parameterized complexity analysis of graph coloring problems"
    - "on problems as hard as cnf sat"
    - "exact algorithms via monotone local search"
    - "powers of tensors and fast matrix multiplication"
    - "faster deterministic feedback vertex set"
    - "solving connectivity problems parameterized by treewidth in single exponential time"

Connected through hyperedge HE-3 (induced by source paper "improved analysis of highest degree branching for feedback vertex set"):
  with members:
    - "experimental evaluation of parameterized algorithms for feedback vertex set"
    - "a naive algorithm for feedback vertex set"
    - "0 1 all csps half integral a path packing and linear time fpt algorithms"
    - "linear time kernelization for feedback vertex set"
    - "half integrality lp branching and fpt algorithms"
    - "faster deterministic feedback vertex set"
    - "solving connectivity problems parameterized by treewidth in single exponential time"
    - "randomized algorithms for the loop cutset problem"

Connected through hyperedge HE-4 (induced by source paper "fpt algorithms for generalized feedback vertex set problems"):
  with members:
    - "detecting feedback vertex sets of size k in o star 2 7 k time"
    - "improved analysis of highest degree branching for feedback vertex set"
    - "smaller parameters for vertex cover kernelization"
    - "directed subset feedback vertex set is fixed parameter tractable"
    - "subset feedback vertex set is fixed parameter tractable"

Connected through hyperedge HE-5 (induced by source paper "an improved fpt algorithm for independent feedback vertex set"):
  with members:
    - "linear time kernelization for feedback vertex set"
    - "simultaneous feedback vertex set a parameterized perspective"
    - "half integrality lp branching and fpt algorithms"
    - "faster deterministic feedback vertex set"
    - "on group feedback vertex set parameterized by the size of the cutset"
    - "representative sets and irrelevant vertices new tools for kernelization"
    - "solving connectivity problems parameterized by treewidth in single exponential time"
    - "subset feedback vertex set is fixed parameter tractable"

Connected through hyperedge HE-6 (induced by source paper "experimental evaluation of parameterized algorithms for feedback vertex set"):
  with members:
    - "a naive algorithm for feedback vertex set"
    - "linear time kernelization for feedback vertex set"
    - "half integrality lp branching and fpt algorithms"
    - "faster deterministic feedback vertex set"
    - "solving connectivity problems parameterized by treewidth in single exponential time"
    - "randomized algorithms for the loop cutset problem"

Connected through hyperedge HE-7 (induced by source paper "a naive algorithm for feedback vertex set"):
  with members:
    - "randomized algorithms for the loop cutset problem"

Connected through hyperedge HE-8 (induced by source paper "irreversible 2 conversion set in graphs of bounded degree"):
  with members:
    - "the maximum time of 2 neighbor bootstrap percolation complexity results"

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)