human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "proving expected sensitivity of probabilistic programs with randomized variable dependent termination time"):
  Abstract: The notion of program sensitivity (aka Lipschitz continuity) specifies that changes in the program input result in proportional changes to the program output. For probabilistic programs the notion is naturally extended to expected sensitivity. A previous approach develops a relational program logic framework for proving expected sensitivity of probabilistic while loops, where the number of iterations is fixed and bounded. In this work, we consider probabilistic while loops where the number of iterations is not fixed, but randomized and depends on the initial input values. We present a sound approach for proving expected sensitivity of such programs. Our sound approach is martingale-based and can be automated through existing martingale-synthesis algorithms. Furthermore, our approach is compositional for sequential composition of while loops under a mild side condition. We demonstrate the effectiveness of our approach on several classical examples from Gambler's Ruin, stochastic hybrid systems and stochastic gradient descent. We also present experimental results showing that our automated approach can handle various probabilistic programs in the literature.

Includes members:
  Member "kantorovich continuity of probabilistic programs":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "proving expected sensitivity of probabilistic programs with randomized execution time")
  Member "new approaches for almost sure termination of probabilistic programs":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "modular verification for almost sure termination of probabilistic programs")
  Member "computational approaches for stochastic shortest path on succinct mdps":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "cost analysis of nondeterministic probabilistic programs")
  Member "bounded expectations resource analysis for probabilistic programs":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "exponential automatic amortized resource analysis")
  Member "proving expected sensitivity of probabilistic programs":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "relational proofs for quantum programs")
  Member "finding polynomial loop invariants for probabilistic programs":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "aiming low is harder inductive proof rules for lower bounds on weakest preexpectations in probabilistic program verification")
  Member "a new proof rule for almost sure termination":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "cost analysis of nondeterministic probabilistic programs")
  Member "a semantic account of metric preservation":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "duet an expressive higher order language and linear type system for statically enforcing differential privacy")

Question: Please tell me which class the source paper 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.PL(Programming Languages)