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: "computing tree decompositions with flowcutter pace 2017 submission"
  Abstract: We describe the algorithm behind our PACE 2017 submission to the heuristic tree decomposition computation track. It was the only competitor to solve all instances and won a tight second place. The algorithm was originally developed in the context of accelerating shortest path computation on road graphs using multilevel partitions. We illustrate how this seemingly unrelated field fits into tree decomposition and parameterized complexity theory.

Connected through hyperedge HE-1 (induced by source paper "finding hamiltonian cycle in graphs of bounded treewidth experimental evaluation"):
  with members:
    - "slightly superexponential parameterized problems"
    - "speeding up dynamic programming with representative sets an experimental evaluation of algorithms for steiner tree on tree decompositions"
    - "fast hamiltonicity checking via bases of perfect matchings"
    - "solving connectivity problems parameterized by treewidth in single exponential time"
    - "determinant sums for undirected hamiltonicity"
    - "known algorithms on graphs of bounded treewidth are probably optimal"
    - "trimmed moebius inversion and graphs of bounded degree"

Connected through hyperedge HE-2 (induced by source paper "fully polynomial time parameterized computations for graphs and matrices of low treewidth"):
  with members:
    - "computing treewidth on the gpu"
    - "on the power of tree depth for fully polynomial fpt algorithms"
    - "positive instance driven dynamic programming for treewidth"
    - "computing maximum flow with augmenting electrical flows"
    - "approximation and fixed parameter subquadratic algorithms for radius and diameter"
    - "polynomial fixed parameter algorithms a case study for longest path on interval graphs"
    - "graph bisection with pareto optimization"
    - "approximate undirected maximum flows in o m polylog n time"

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)