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: "exact algorithms via monotone local search"
  Abstract: We give a new general approach for designing exact exponential-time algorithms for subset problems. In a subset problem the input implicitly describes a family of sets over a universe of size n and the task is to determine whether the family contains at least one set. Our approach is based on "monotone local search", where the goal is to extend a partial solution to a solution by adding as few elements as possible. More formally, in the extension problem we are also given as input a subset X of the universe and an integer k. The task is to determine whether one can add at most k elements to X to obtain a set in the (implicitly defined) family. Our main result is that an O*(c^k) time algorithm for the extension problem immediately yields a randomized algorithm for finding a solution of any size with running time O*((2-1/c)^n). #R##N#In many cases, the extension problem can be reduced to simply finding a solution of size at most k. Furthermore, efficient algorithms for finding small solutions have been extensively studied in the field of parameterized algorithms. Directly applying these algorithms, our theorem yields in one stroke significant improvements over the best known exponential-time algorithms for several well-studied problems, including d-Hitting Set, Feedback Vertex Set, Node Unique Label Cover, and Weighted d-SAT. Our results demonstrate an interesting and very concrete connection between parameterized algorithms and exact exponential-time algorithms. #R##N#We also show how to derandomize our algorithms at the cost of a subexponential multiplicative factor in the running time. Our derandomization is based on an efficient construction of a new pseudo-random object that might be of independent interest. Finally, we extend our methods to establish new combinatorial upper bounds and develop enumeration algorithms.

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"
    - "improved bounds for the flat wall theorem"

Connected through hyperedge HE-2 (induced by source paper "reducing topological minor containment to the unique linkage theorem"):
  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"
    - "linear kernels for edge deletion problems to immersion closed graph classes"
    - "bidimensionality and kernels"

Connected through hyperedge HE-3 (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"
    - "on feedback vertex set new measure and new structures"
    - "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-4 (induced by source paper "node multiway cut and subset feedback vertex set on graphs of bounded mim width"):
  with members:
    - "subset feedback vertex set on graphs of bounded independent set size"
    - "rank based approach on graphs with structured neighborhood"
    - "fast exact algorithms for some connectivity problems parametrized by clique width"
    - "on the tractability of optimization problems on h graphs"
    - "polynomial time algorithms for the subset feedback vertex set problem on interval graphs and permutation graphs"
    - "a unified polynomial time algorithm for feedback vertex set on graphs of bounded mim width"
    - "a randomized polynomial kernel for subset feedback vertex set"
    - "faster algorithms for vertex partitioning problems parameterized by clique width"

Connected through hyperedge HE-5 (induced by source paper "subexponential time algorithms for finding large induced sparse subgraphs"):
  with members:
    - "deleting vertices to graphs of bounded genus"
    - "polynomial time algorithm for maximum weight independent set on p_6 free graphs"
    - "tight running time lower bounds for vertex deletion problems"
    - "hitting forbidden subgraphs in graphs of bounded treewidth"
    - "large induced subgraphs via triangulations and cmso"
    - "largest chordal and interval subgraphs faster than 2 n"
    - "finding a maximum induced degenerate subgraph faster than 2 n"
    - "problems parameterized by treewidth tractable in single exponential time a logical approach"

Connected through hyperedge HE-6 (induced by source paper "subset feedback vertex set in chordal and split graphs"):
  with members:
    - "a randomized polynomial kernel for subset feedback vertex set"
    - "half integrality lp branching and fpt algorithms"
    - "directed subset feedback vertex set is fixed parameter tractable"
    - "hitting forbidden minors approximation and kernelization"
    - "subset feedback vertex set is fixed parameter tractable"

Connected through hyperedge HE-7 (induced by source paper "enumeration of preferred extensions in almost oriented digraphs"):
  with members:
    - "exact algorithms via multivariate subroutines"
    - "computing preferred extensions in abstract argumentation a sat based approach"
    - "value based argumentation frameworks"

Connected through hyperedge HE-8 (induced by source paper "faster fpt algorithm for 5 path vertex cover"):
  with members:
    - "an o 2 619 k algorithm for 4 path vertex cover"
    - "parameterized algorithm for 3 path vertex cover"
    - "a shortcut to sun flowers kernels in logarithmic space or linear time"

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)