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: "algorithm for finding k vertex out trees and its application to k internal out branching problem"
  Abstract: An out-tree $T$ is an oriented tree with only one vertex of in-degree zero. A vertex $x$ of $T$ is internal if its out-degree is positive. We design randomized and deterministic algorithms for deciding whether an input digraph contains a given out-tree with $k$ vertices. The algorithms are of runtime $O^*(5.704^k)$ and $O^*(5.704^{k(1+o(1))})$, respectively. We apply the deterministic algorithm to obtain a deterministic algorithm of runtime $O^*(c^k)$, where $c$ is a constant, for deciding whether an input digraph contains a spanning out-tree with at least $k$ internal vertices. This answers in affirmative a question of Gutin, Razgon and Kim (Proc. AAIM'08).

Connected through hyperedge HE-1 (induced by source paper "designing deterministic polynomial space algorithms by color coding multivariate polynomials"):
  with members:
    - "directed hamiltonicity and out branchings via generalized laplacians"
    - "spotting trees with few leaves"
    - "complexity results for rainbow matchings"
    - "fast algorithms for parameterized problems with relaxed disjointness constraints"
    - "representative families a unified tradeoff based approach"
    - "mixing color coding related techniques"
    - "abusing the tutte matrix an algebraic instance compression for the k set cycle problem"
    - "narrow sieves for parameterized paths and packings"

Connected through hyperedge HE-2 (induced by source paper "approximation algorithms for the maximum weight internal spanning tree problem"):
  with members:
    - "an approximation algorithm for maximum internal spanning tree"
    - "a 2k vertex kernel for maximum internal spanning tree"
    - "a linear vertex kernel for maximum internal spanning tree"

Connected through hyperedge HE-3 (induced by source paper "an approximation algorithm for maximum internal spanning tree"):
  with members:
    - "a 4 3 approximation algorithm for finding a spanning tree to maximize its internal vertices"
    - "a 2k vertex kernel for maximum internal spanning tree"
    - "a linear vertex kernel for maximum internal spanning tree"

Connected through hyperedge HE-4 (induced by source paper "spotting trees with few leaves"):
  with members:
    - "representative sets of product families"
    - "representative families a unified tradeoff based approach"
    - "a 2k vertex kernel for maximum internal spanning tree"
    - "mixing color coding related techniques"
    - "solving connectivity problems parameterized by treewidth in single exponential time"
    - "narrow sieves for parameterized paths and packings"
    - "determinant sums for undirected hamiltonicity"
    - "a linear vertex kernel for maximum internal spanning tree"

Connected through hyperedge HE-5 (induced by source paper "mixing color coding related techniques"):
  with members:
    - "representative sets of product families"
    - "representative families a unified tradeoff based approach"
    - "a 2k vertex kernel for maximum internal spanning tree"
    - "deterministic parameterized algorithms for matching and packing problems"
    - "narrow sieves for parameterized paths and packings"
    - "determinant sums for undirected hamiltonicity"
    - "a linear vertex kernel for maximum internal spanning tree"
    - "minimum leaf out branching and related problems"

Connected through hyperedge HE-6 (induced by source paper "a multivariate framework for weighted fpt algorithms"):
  with members:
    - "representative families a unified tradeoff based approach"
    - "minimum bisection is fixed parameter tractable"
    - "deterministic parameterized connected vertex cover"
    - "vertex cover kernelization revisited upper and lower bounds for a refined parameter"
    - "determinant sums for undirected hamiltonicity"
    - "a linear vertex kernel for maximum internal spanning tree"
    - "minimum leaf out branching and related problems"

Connected through hyperedge HE-7 (induced by source paper "a 2k vertex kernel for maximum internal spanning tree"):
  with members:
    - "representative families a unified tradeoff based approach"
    - "a linear vertex kernel for maximum internal spanning tree"
    - "minimum leaf out branching and related problems"

Connected through hyperedge HE-8 (induced by source paper "faster computation of representative families for uniform matroids with applications"):
  with members:
    - "approximating the maxcover problem with bounded frequencies in fpt time"
    - "a linear vertex kernel for maximum internal spanning tree"

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)