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 "solving weighted and counting variants of connectivity problems parameterized by treewidth deterministically in single exponential time"):
  Abstract: It is well known that many local graph problems, like Vertex Cover and Dominating Set, can be solved in 2^{O(tw)}|V|^{O(1)} time for graphs G=(V,E) with a given tree decomposition of width tw. However, for nonlocal problems, like the fundamental class of connectivity problems, for a long time we did not know how to do this faster than tw^{O(tw)}|V|^{O(1)}. Recently, Cygan et al. (FOCS 2011) presented Monte Carlo algorithms for a wide range of connectivity problems running in time $c^{tw}|V|^{O(1)} for a small constant c, e.g., for Hamiltonian Cycle and Steiner tree. Naturally, this raises the question whether randomization is necessary to achieve this runtime; furthermore, it is desirable to also solve counting and weighted versions (the latter without incurring a pseudo-polynomial cost in terms of the weights). #R##N#We present two new approaches rooted in linear algebra, based on matrix rank and determinants, which provide deterministic c^{tw}|V|^{O(1)} time algorithms, also for weighted and counting versions. For example, in this time we can solve the traveling salesman problem or count the number of Hamiltonian cycles. The rank-based ideas provide a rather general approach for speeding up even straightforward dynamic programming formulations by identifying "small" sets of representative partial solutions; we focus on the case of expressing connectivity via sets of partitions, but the essential ideas should have further applications. The determinant-based approach uses the matrix tree theorem for deriving closed formulas for counting versions of connectivity problems; we show how to evaluate those formulas via dynamic programming.

Includes members:
  Member "on feedback vertex set new measure and new structures":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "hitting long directed cycles is fixed parameter tractable")
  Member "fast hamiltonicity checking via bases of perfect matchings":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "subexponential parameterized algorithms and kernelization on almost chordal graphs")
  Member "solving connectivity problems parameterized by treewidth in single exponential time":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "hamiltonian cycle parameterized by treedepth in single exponential time and polynomial space")
  Member "determinant sums for undirected hamiltonicity":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "finding temporal patterns using algebraic fingerprints")
  Member "known algorithms on graphs of bounded treewidth are probably optimal":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "on the complexity of finding large odd induced subgraphs and odd colorings")
  Member "the traveling salesman problem for cubic graphs":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "an exact algorithm for tsp in degree 3 graphs via circuit procedure and amortization on connectivity structure")

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)