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 pitfalls of verifying floating point computations"
  Abstract: Current critical systems often use a lot of floating-point computations, and thus the testing or static analysis of programs containing floating-point operators has become a priority. However, correctly defining the semantics of common implementations of floating-point is tricky, because semantics may change according to many factors beyond source-code level, such as choices made by compilers. We here give concrete examples of problems that can appear and solutions for implementing in analysis software.

Connected through hyperedge HE-1 (induced by source paper "abstract compilation for verification of numerical accuracy properties"):
  with members:
    - "eliminating unstable tests in floating point programs"
    - "finding root causes of floating point error with herbgrind"
    - "verificarlo checking floating point accuracy through monte carlo arithmetic"
    - "robustness analysis of finite precision implementations"
    - "certification of bounds on expressions involving rounded operators"

Connected through hyperedge HE-2 (induced by source paper "internal versus external balancing in the evaluation of graph based number types"):
  with members:
    - "on error representation in exact decisions number types"
    - "restructuring expression dags for efficient parallelization"
    - "multithreading for the expression dag based number type real_algebraic"
    - "balancing expression dags for more efficient lazy adaptive evaluation"
    - "a note on the complexity of computing the number of reachable vertices in a digraph"

Connected through hyperedge HE-3 (induced by source paper "an open source c implementation of multi threaded gaussian mixture models k means and expectation maximisation"):
  with members:
    - "exploiting temporal information for dcnn based fine grained object classification"
    - "comparative evaluation of action recognition methods via riemannian manifolds fisher vectors and gmms ideal and challenging conditions"
    - "modelling local deep convolutional neural network features to improve fine grained image classification"
    - "on robust face recognition via sparse coding the good the bad and the ugly"
    - "improved foreground detection via block based classifier cascade with probabilistic decision integration"
    - "mlpack a scalable c machine learning library"
    - "revisiting k means new algorithms via bayesian nonparametrics"

Connected through hyperedge HE-4 (induced by source paper "semantics logic and verification of exact real computation"):
  with members:
    - "dividing by zero how bad is it really"
    - "satisfiability of cross product terms is complete for real nondeterministic polytime blum shub smale machines"
    - "complexity theory for operators in analysis"
    - "quantifier elimination for the reals with a predicate for the powers of two"
    - "abstract versus concrete computation on metric partial algebras"

Connected through hyperedge HE-5 (induced by source paper "automatic modular abstractions for template numerical constraints"):
  with members:
    - "a quantifier elimination algorithm for linear real arithmetic"
    - "automatic modular abstractions for linear constraints"
    - "relational abstract domains for the detection of floating point run time errors"
    - "accelerated data flow analysis"
    - "the octagon abstract domain"
    - "symbolic methods to enhance the precision of numerical abstract domains"
    - "a static analyzer for large safety critical software"

Connected through hyperedge HE-6 (induced by source paper "automatic modular abstractions for linear constraints"):
  with members:
    - "a quantifier elimination algorithm for linear real arithmetic"
    - "relational abstract domains for the detection of floating point run time errors"
    - "the octagon abstract domain"
    - "a static analyzer for large safety critical software"

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.PL(Programming Languages)