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: "efficiently intertwining widening and narrowing"
  Abstract: Non-trivial analysis problems require posets with infinite ascending and descending chains. In order to compute reasonably precise post-fixpoints of the resulting systems of equations, Cousot and Cousot have suggested accelerated fixpoint iteration by means of widening and narrowing. #R##N#The strict separation into phases, however, may unnecessarily give up precision that cannot be recovered later, as over-approximated interim results have to be fully propagated through the equation the system. Additionally, classical two-phased approach is not suitable for equation systems with infinitely many unknowns---where demand driven solving must be used. Construction of an intertwined approach must be able to answer when it is safe to apply narrowing---or when widening must be applied. In general, this is a difficult problem. In case the right-hand sides of equations are monotonic, however, we can always apply narrowing whenever we have reached a post-fixpoint for an equation. The assumption of monotonicity, though, is not met in presence of widening. It is also not met by equation systems corresponding to context-sensitive inter-procedural analysis, possibly combining context-sensitive analysis of local information with flow-insensitive analysis of globals. #R##N#As a remedy, we present a novel operator that combines a given widening operator with a given narrowing operator. We present adapted versions of round-robin as well as of worklist iteration, local and side-effecting solving algorithms for the combined operator and prove that the resulting solvers always return sound results and are guaranteed to terminate for monotonic systems whenever only finitely many unknowns (constraint variables) are encountered. Practical remedies are proposed for termination in the non-monotonic case.

Connected through hyperedge HE-1 (induced by source paper "deterministic parallel fixpoint computation"):
  with members:
    - "abstract interpretation with higher dimensional ellipsoids and conic extrapolation"
    - "a new numerical abstract domain based on difference bound matrices"
    - "relational abstract domains for the detection of floating point run time errors"
    - "the octagon abstract domain"
    - "the parallel implementation of the astree static analyzer"

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)