human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "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.

Includes members:
  Member "representative sets of product families":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "hitting long directed cycles is fixed parameter tractable")
  Member "representative families a unified tradeoff based approach":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "hitting long directed cycles is fixed parameter tractable")
  Member "a 2k vertex kernel for maximum internal spanning tree":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "approximation algorithms for the maximum weight internal spanning tree problem")
  Member "mixing color coding related techniques":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "parameterized complexity of partial scheduling")
  Member "solving connectivity problems parameterized by treewidth in single exponential time":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "hamiltonian cycle parameterized by treedepth in single exponential time and polynomial space")
  Member "narrow sieves for parameterized paths and packings":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "finding temporal patterns using algebraic fingerprints")
  Member "determinant sums for undirected hamiltonicity":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "finding temporal patterns using algebraic fingerprints")
  Member "algorithm for finding k vertex out trees and its application to k internal out branching problem":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "designing deterministic polynomial space algorithms by color coding multivariate polynomials")

Question: Please tell me which class the source paper 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)