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: "faster deterministic feedback vertex set"
  Abstract: We present two new deterministic algorithms for the Feedback Vertex Set problem parameterized by the solution size. We begin with a simple algorithm, which runs in O*((2 + \phi)^k) time, where \phi < 1.619 is the golden ratio. It already surpasses the previously fastest O*((1+2sqrt(2))^k)-time deterministic algorithm due to Cao et al. [SWAT 2010]. In our developments we follow the approach of Cao et al., however, thanks to a new reduction rule, we obtain not only better dependency on the parameter in the running time, but also a solution with simple analysis and only a single branching rule. Then, we present a modification of the algorithm which, using a more involved set of branching rules, achieves O*(3.592^k) running time.

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"
    - "on feedback vertex set new measure and new structures"
    - "a randomized algorithm for long directed cycle"
    - "representative sets of product families"
    - "representative families a unified tradeoff based approach"
    - "the directed grid theorem"
    - "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"
    - "on feedback vertex set new measure and new structures"
    - "powers of tensors and fast matrix multiplication"
    - "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"
    - "on feedback vertex set new measure and new structures"
    - "half integrality lp branching and fpt algorithms"
    - "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 diverse collections of hitting sets"):
  with members:
    - "diversity in combinatorial optimization"
    - "preparing for the unexpected diversity improves planning resilience in evolutionary algorithms"
    - "discrepancy based evolutionary diversity optimization"
    - "maximum volume subset selection for anchored boxes"
    - "cutset sampling with likelihood weighting"
    - "approximation algorithms for secondary spectrum auctions"
    - "minimal change integrity maintenance using tuple deletions"

Connected through hyperedge HE-5 (induced by source paper "structural parameterization for graph deletion problems over data streams"):
  with members:
    - "on the streaming complexity of fundamental geometric problems"
    - "tight bounds for single pass streaming complexity of the set cover problem"
    - "interval deletion is fixed parameter tractable"
    - "linear kernels and single exponential algorithms via protrusion decompositions"
    - "preprocessing subgraph and minor problems when does a small vertex cover help"
    - "hitting forbidden minors approximation and kernelization"

Connected through hyperedge HE-6 (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"
    - "on feedback vertex set new measure and new structures"
    - "half integrality lp branching and fpt algorithms"
    - "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-7 (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"
    - "on feedback vertex set new measure and new structures"
    - "half integrality lp branching and fpt algorithms"
    - "solving connectivity problems parameterized by treewidth in single exponential time"
    - "randomized algorithms for the loop cutset problem"

Connected through hyperedge HE-8 (induced by source paper "a parameterized complexity view on collapsing k cores"):
  with members:
    - "linear time kernelization for feedback vertex set"
    - "social resilience in online communities the autopsy of friendster"
    - "preventing unraveling in social networks gets harder"
    - "parameterized complexity of the anchored k core problem for directed 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)