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 "fully polynomial time parameterized computations for graphs and matrices of low treewidth"):
  Abstract: We investigate the complexity of several fundamental polynomial-time solvable problems on graphs and on matrices, when the given instance has low treewidth; in the case of matrices, we consider the treewidth of the graph formed by non-zero entries. In each of the considered cases, the best known algorithms working on general graphs run in polynomial time, however the exponent of the polynomial is large. Therefore, our main goal is to construct algorithms with running time of the form $\textrm{poly}(k)\cdot n$ or $\textrm{poly}(k)\cdot n\log n$, where $k$ is the width of the tree decomposition given on the input. Such procedures would outperform the best known algorithms for the considered problems already for moderate values of the treewidth, like $O(n^{1/c})$ for some small constant $c$. #R##N#Our results include: #R##N#-- an algorithm for computing the determinant and the rank of an $n\times n$ matrix using $O(k^3\cdot n)$ time and arithmetic operations; #R##N#-- an algorithm for solving a system of linear equations using $O(k^3\cdot n)$ time and arithmetic operations; #R##N#-- an $O(k^3\cdot n\log n)$-time randomized algorithm for finding the cardinality of a maximum matching in a graph; #R##N#-- an $O(k^4\cdot n\log^2 n)$-time randomized algorithm for constructing a maximum matching in a graph; #R##N#-- an $O(k^2\cdot n\log n)$-time algorithm for finding a maximum vertex flow in a directed graph. #R##N#Moreover, we give an approximation algorithm for treewidth with time complexity suited to the running times as above. Namely, the algorithm, when given a graph $G$ and integer $k$, runs in time $O(k^7\cdot n\log n)$ and either correctly reports that the treewidth of $G$ is larger than $k$, or constructs a tree decomposition of $G$ of width $O(k^2)$.

Includes members:
  Member "computing tree decompositions with flowcutter pace 2017 submission":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "finding hamiltonian cycle in graphs of bounded treewidth experimental evaluation")
  Member "computing treewidth on the gpu":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "benchmarking treewidth as a practical component of tensor network simulations")
  Member "on the power of tree depth for fully polynomial fpt algorithms":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "on adaptive algorithms for maximum matching")
  Member "positive instance driven dynamic programming for treewidth":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "finding all global minimum cuts in practice")
  Member "computing maximum flow with augmenting electrical flows":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "faster divergence maximization for faster maximum flow")
  Member "approximation and fixed parameter subquadratic algorithms for radius and diameter":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "parameterized fine grained reductions")
  Member "polynomial fixed parameter algorithms a case study for longest path on interval graphs":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "computing maximum matchings in temporal graphs")
  Member "graph bisection with pareto optimization":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "load balanced bottleneck objectives in process mapping")

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)