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: "polynomial invariant generation for non deterministic recursive programs"
  Abstract: We present a sound and complete method to generate inductive invariants consisting of polynomial inequalities for programs with polynomial updates. Our method is based on Positivstellensatze and an algorithm of Grigor'ev and Vorobjov [24] for solving systems of polynomial inequalities. To the best of our knowledge, this is the first method to guarantee completeness for polynomial inequality invariants. The worst-case complexity of our approach is subexponential, whereas the worst-case complexity of the previously-known complete method (Colon et al [12], CAV 2003), which could only handle linear invariants, is exponential. We also present experimental results on several academic examples that require polynomial invariants.

Connected through hyperedge HE-1 (induced by source paper "automatic generation of moment based invariants for prob solvable loops"):
  with members:
    - "tail probabilities for randomized program runtimes via martingales for higher moments"
    - "aligator jl a julia package for loop invariant generation"
    - "finding polynomial loop invariants for probabilistic programs"
    - "a new proof rule for almost sure termination"
    - "a storm is coming a modern probabilistic model checker"
    - "synthesizing probabilistic invariants via doob s decomposition"
    - "bounded model checking for probabilistic programs"
    - "counterexample guided polynomial loop invariant generation by lagrange interpolation"

Connected through hyperedge HE-2 (induced by source paper "polynomial probabilistic invariants and the optional stopping theorem"):
  with members:
    - "compositional analysis for almost sure termination of probabilistic programs"
    - "aiming low is harder inductive proof rules for lower bounds on weakest preexpectations in probabilistic program verification"
    - "tail probabilities for randomized program runtimes via martingales for higher moments"
    - "finding polynomial loop invariants for probabilistic programs"
    - "weakest precondition reasoning for expected run times of probabilistic programs"
    - "synthesizing probabilistic invariants via doob s decomposition"
    - "counterexample guided polynomial loop invariant generation by lagrange interpolation"

Connected through hyperedge HE-3 (induced by source paper "non polynomial worst case analysis of recursive programs"):
  with members:
    - "termination of nondeterministic recursive probabilistic programs"
    - "the complexity of interaction"
    - "termination analysis of probabilistic programs through positivstellensatz s"
    - "reasoning about recursive probabilistic programs"
    - "a simple and scalable static analysis for bound analysis and amortized complexity analysis"

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.LO(Logic in Computer Science)