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: "the complexity of the simplex method"
  Abstract: The simplex method is a well-studied and widely-used pivoting method for solving linear programs. When Dantzig originally formulated the simplex method, he gave a natural pivot rule that pivots into the basis a variable with the most violated reduced cost. In their seminal work, Klee and Minty showed that this pivot rule takes exponential time in the worst case. We prove two main results on the simplex method. Firstly, we show that it is PSPACE-complete to find the solution that is computed by the simplex method using Dantzig's pivot rule. Secondly, we prove that deciding whether Dantzig's rule ever chooses a specific variable to enter the basis is PSPACE-complete. We use the known connection between Markov decision processes (MDPs) and linear programming, and an equivalence between Dantzig's pivot rule and a natural variant of policy iteration for average-reward MDPs. We construct MDPs and show PSPACE-completeness results for single-switch policy iteration, which in turn imply our main results for the simplex method.

Connected through hyperedge HE-1 (induced by source paper "on the complexity of value iteration"):
  with members:
    - "sound value iteration"
    - "the reachability problem for petri nets is not elementary"
    - "variance reduced value iteration and faster algorithms for solving markov decision processes"
    - "value iteration networks"
    - "robust synchronization in markov decision processes"
    - "on the complexity of solving markov decision problems"
    - "on the complexity of policy iteration"
    - "the complexity of plan existence and evaluation in probabilistic domains"

Connected through hyperedge HE-2 (induced by source paper "on the computational power of online gradient descent"):
  with members:
    - "introduction to online convex optimization"
    - "stochastic gradient descent performs variational inference converges to limit cycles for deep networks"
    - "on the computational complexity of limit cycles in dynamical systems"
    - "on simplex pivoting rules and complexity theory"
    - "the simplex algorithm is np mighty"
    - "the complexity of the homotopy method equilibrium selection and lemke howson solutions"

Connected through hyperedge HE-3 (induced by source paper "complexity of single swap heuristics for metric facility location and related problem"):
  with members:
    - "local search yields a ptas for k means in doubling metrics"
    - "on simplex pivoting rules and complexity theory"
    - "k means requires exponentially many iterations even in the plane"

Connected through hyperedge HE-4 (induced by source paper "the complexity of all switches strategy improvement"):
  with members:
    - "on simplex pivoting rules and complexity theory"
    - "the simplex algorithm is np mighty"
    - "an exponential lower bound for the latest deterministic strategy iteration algorithms"
    - "non oblivious strategy improvement"
    - "the complexity of the homotopy method equilibrium selection and lemke howson solutions"
    - "exponential lower bounds for policy iteration"
    - "linear complementarity algorithms for infinite games"

Connected through hyperedge HE-5 (induced by source paper "the simplex algorithm is np mighty"):
  with members:
    - "the complexity of all switches strategy improvement"
    - "on simplex pivoting rules and complexity theory"
    - "the complexity of the homotopy method equilibrium selection and lemke howson solutions"
    - "smoothed analysis of algorithms why the simplex algorithm usually takes polynomial 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)