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: "spotting trees with few leaves"
  Abstract: We show two results related to the Hamiltonicity and $k$-Path algorithms in undirected graphs by Bj\"orklund [FOCS'10], and Bj\"orklund et al., [arXiv'10]. First, we demonstrate that the technique used can be generalized to finding some $k$-vertex tree with $l$ leaves in an $n$-vertex undirected graph in $O^*(1.657^k2^{l/2})$ time. It can be applied as a subroutine to solve the $k$-Internal Spanning Tree ($k$-IST) problem in $O^*(\min(3.455^k, 1.946^n))$ time using polynomial space, improving upon previous algorithms for this problem. In particular, for the first time we break the natural barrier of $O^*(2^n)$. Second, we show that the iterated random bipartition employed by the algorithm can be improved whenever the host graph admits a vertex coloring with few colors; it can be an ordinary proper vertex coloring, a fractional vertex coloring, or a vector coloring. In effect, we show improved bounds for $k$-Path and Hamiltonicity in any graph of maximum degree $\Delta=4,\ldots,12$ or with vector chromatic number at most 8.

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"
    - "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"
    - "determinant sums for undirected hamiltonicity"

Connected through hyperedge HE-2 (induced by source paper "directed hamiltonicity and out branchings via generalized laplacians"):
  with members:
    - "on problems as hard as cnf sat"
    - "fast algorithms for parameterized problems with relaxed disjointness constraints"
    - "mixing color coding related techniques"
    - "faster exponential time algorithms in graphs of bounded average degree"
    - "the parity of directed hamiltonian cycles"
    - "a new direction for counting perfect matchings"
    - "below all subsets for some permutational counting problems"
    - "fast hamiltonicity checking via bases of perfect matchings"

Connected through hyperedge HE-3 (induced by source paper "narrow sieves for parameterized paths and packings"):
  with members:
    - "mixing color coding related techniques"
    - "determinant sums for undirected hamiltonicity"

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)