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: "counterexample guided polynomial loop invariant generation by lagrange interpolation"
  Abstract: We apply multivariate Lagrange interpolation to synthesize polynomial quantitative loop invariants for probabilistic programs. We reduce the computation of an quantitative loop invariant to solving constraints over program variables and unknown coefficients. Lagrange interpolation allows us to find constraints with less unknown coefficients. Counterexample-guided refinement furthermore generates linear constraints that pinpoint the desired quantitative invariants. We evaluate our technique by several case studies with polynomial quantitative loop invariants in the experiments.

Connected through hyperedge HE-1 (induced by source paper "aiming low is harder inductive proof rules for lower bounds on weakest preexpectations in probabilistic program verification"):
  with members:
    - "quantitative separation logic a logic for reasoning about probabilistic pointer programs"
    - "on the termination problem for probabilistic higher order recursive programs"
    - "bounded expectations resource analysis for probabilistic programs"
    - "termination of nondeterministic recursive probabilistic programs"
    - "finding polynomial loop invariants for probabilistic programs"
    - "a new proof rule for almost sure termination"
    - "a weakest pre expectation semantics for mixed sign expectations"
    - "healthiness from duality"

Connected through hyperedge HE-2 (induced by source paper "automatic generation of moment based invariants for prob solvable loops"):
  with members:
    - "polynomial invariant generation for non deterministic recursive programs"
    - "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"

Connected through hyperedge HE-3 (induced by source paper "polynomial probabilistic invariants and the optional stopping theorem"):
  with members:
    - "polynomial invariant generation for non deterministic recursive programs"
    - "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"

Connected through hyperedge HE-4 (induced by source paper "neuro symbolic execution the feasibility of an inductive approach to symbolic execution"):
  with members:
    - "a counterexample guided approach to finding numerical invariants"
    - "angora efficient fuzzing by principled search"
    - "loopinvgen a loop invariant generator based on precondition inference"
    - "end to end learning for self driving cars"
    - "a continuum among logarithmic linear and exponential functions and its potential to improve generalization in neural networks"
    - "an overview of gradient descent optimization algorithms"
    - "tensorflow a system for large scale machine learning"
    - "the limitations of deep learning in adversarial settings"

Connected through hyperedge HE-5 (induced by source paper "robust invariant sets computation for switched discrete time polynomial systems"):
  with members:
    - "a one step approach to computing a polytopic robust positively invariant set"

Connected through hyperedge HE-6 (induced by source paper "finding polynomial loop invariants for probabilistic programs"):
  with members:
    - "termination analysis of probabilistic programs through positivstellensatz s"
    - "synthesizing probabilistic invariants via doob s decomposition"
    - "on the hardness of almost sure termination"
    - "generating non linear interpolants by semidefinite programming"
    - "proving inequalities and solving global optimization problems via simplified cad projection"

Connected through hyperedge HE-7 (induced by source paper "synthesizing probabilistic invariants via doob s decomposition"):
  with members:
    - "weakest precondition reasoning for expected run times of probabilistic programs"
    - "proving termination of probabilistic programs using patterns"
    - "the octagon abstract domain"

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.SE(Software Engineering)