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: "new approaches for almost sure termination of probabilistic programs"
  Abstract: We study the almost-sure termination problem for probabilistic programs. First, we show that supermartingales with lower bounds on conditional absolute difference provide a sound approach for the almost-sure termination problem. Moreover, using this approach we can obtain explicit optimal bounds on tail probabilities of non-termination within a given number of steps. Second, we present a new approach based on Central Limit Theorem for the almost-sure termination problem, and show that this approach can establish almost-sure termination of programs which none of the existing approaches can handle. Finally, we discuss algorithmic approaches for the two above methods that lead to automated analysis techniques for almost-sure termination of probabilistic programs.

Connected through hyperedge HE-1 (induced by source paper "modular verification for almost sure termination of probabilistic programs"):
  with members:
    - "cost analysis of nondeterministic probabilistic programs"
    - "quantitative separation logic a logic for reasoning about probabilistic pointer programs"
    - "computational approaches for stochastic shortest path on succinct mdps"
    - "bounded expectations resource analysis for probabilistic programs"
    - "termination of nondeterministic recursive probabilistic programs"
    - "a new proof rule for almost sure termination"
    - "lexicographic ranking supermartingales an efficient approach to termination of probabilistic programs"
    - "cantor meets scott semantic foundations for probabilistic networks"

Connected through hyperedge HE-2 (induced by source paper "proving expected sensitivity of probabilistic programs with randomized variable dependent termination time"):
  with members:
    - "kantorovich continuity of probabilistic programs"
    - "computational approaches for stochastic shortest path on succinct mdps"
    - "bounded expectations resource analysis for probabilistic programs"
    - "proving expected sensitivity of probabilistic programs"
    - "finding polynomial loop invariants for probabilistic programs"
    - "a new proof rule for almost sure termination"
    - "a semantic account of metric preservation"
    - "lexicographic ranking supermartingales an efficient approach to termination of probabilistic programs"

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)