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: "two results on slime mold computations"
  Abstract: Abstract   We present two results on slime mold computations. In wet-lab experiments by Nakagaki et al. (2000)  [1]  the slime mold Physarum polycephalum demonstrated its ability to solve shortest path problems. Biologists proposed a mathematical model, a system of differential equations, for the slime's adaption process (Tero et al., 2007)  [3] . It was shown that the process convergences to the shortest path (Bonifaci et al., 2012)  [5]  for all graphs. We show that the dynamics actually converges for a much wider class of problems, namely undirected linear programs with a non-negative cost vector.  Combinatorial optimization researchers took the dynamics describing slime behavior as an inspiration for an optimization method and showed that its discretization can e-approximately solve linear programs with positive cost vector (Straszak and Vishnoi, 2016)  [14] . Their analysis requires a feasible starting point, a step size depending linearly on e, and a number of steps with quartic dependence on     opt   /  (  e  Φ  )   , where Φ is the difference between the smallest cost of a non-optimal basic feasible solution and the optimal cost (opt).  We give a refined analysis showing that the dynamics initialized with any strongly dominating point converges to the set of optimal solutions. Moreover, we strengthen the convergence rate bounds and prove that the step size is independent of e, and the number of steps depends logarithmically on    1  /  e    and quadratically on     opt   /  Φ   .

Connected through hyperedge HE-1 (induced by source paper "a laplacian approach to ell_1 norm minimization"):
  with members:
    - "irls and slime mold equivalence and convergence"
    - "physarum can compute shortest paths"
    - "optimization with sparsity inducing penalties"
    - "runtime guarantees for regression problems"
    - "electrical flows laplacian systems and faster approximation of maximum flow in undirected graphs"

Connected through hyperedge HE-2 (induced by source paper "convergence of the non uniform physarum dynamics"):
  with members:
    - "irls and slime mold equivalence and convergence"
    - "on a natural dynamics for linear programming"
    - "physarum can compute shortest paths"

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)