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 "fooling functions of halfspaces under product distributions"):
  Abstract: We construct pseudorandom generators that fool functions of halfspaces (threshold functions) under a very broad class of product distributions. This class includes not only familiar cases such as the uniform distribution on the discrete cube, the uniform distribution on the solid cube, and the multivariate Gaussian distribution, but also includes any product of discrete distributions with probabilities bounded away from 0. #R##N#Our first main result shows that a recent pseudorandom generator construction of Meka and Zuckerman [MZ09], when suitably modifed, can fool arbitrary functions of d halfspaces under product distributions where each coordinate has bounded fourth moment. To eps-fool any size-s, depth-d decision tree of halfspaces, our pseudorandom generator uses seed length O((d log(ds/eps)+log n) log(ds/eps)). For monotone functions of d halfspaces, the seed length can be improved to O((d log(d/eps)+log n) log(d/eps)). We get better bounds for larger eps; for example, to 1/polylog(n)-fool all monotone functions of (log n)= log log n halfspaces, our generator requires a seed of length just O(log n). Our second main result generalizes the work of Diakonikolas et al. [DGJ+09] to show that bounded independence suffices to fool functions of halfspaces under product distributions. Assuming each coordinate satisfies a certain stronger moment condition, we show that any function computable by a size-s, depth-d decision tree of halfspaces is eps-fooled by O(d^4s^2/eps^2)-wise independence.

Includes members:
  Member "an invariance principle for polytopes":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "kruskal katona for convex sets with applications")
  Member "agnostic learning of monomials by halfspaces is hard":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "solving empirical risk minimization in the current matrix multiplication time")
  Member "bounded independence fools halfspaces":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "list decodable subspace recovery via sum of squares")
  Member "polynomial threshold functions structure approximation and pseudorandomness":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a ptas for agnostically learning halfspaces")
  Member "pseudorandom generators for polynomial threshold functions":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "degree d chow parameters robustly determine degree d ptfs and algorithmic applications")
  Member "bounded independence fools degree 2 threshold functions":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "stable sparse subspace embedding for dimensionality reduction")

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.CC(Computational Complexity)