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 "a regularity lemma and low weight approximators for low degree polynomial threshold functions"):
  Abstract: We give a "regularity lemma" for degree-d polynomial threshold functions (PTFs) over the Boolean cube {-1,1}^n. This result shows that every degree-d PTF can be decomposed into a constant number of subfunctions such that almost all of the subfunctions are close to being regular PTFs. Here a "regular PTF is a PTF sign(p(x)) where the influence of each variable on the polynomial p(x) is a small fraction of the total influence of p. #R##N#As an application of this regularity lemma, we prove that for any constants d \geq 1, \eps \geq 0, every degree-d PTF over n variables has can be approximated to accuracy eps by a constant-degree PTF that has integer weights of total magnitude O(n^d). This weight bound is shown to be optimal up to constant factors.

Includes members:
  Member "k independent gaussians fool polynomial threshold functions":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "fooling polytopes")
  Member "average sensitivity and noise sensitivity of polynomial threshold functions":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "kruskal katona for convex sets with applications")
  Member "improved approximation of linear threshold functions":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "nearly tight bounds for robust proper learning of halfspaces with a margin")
  Member "bounded independence fools halfspaces":
    also connected through other hyperedges:
      - Hyperedge HE-4 (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-5 (induced by source paper "a ptas for agnostically learning halfspaces")
  Member "bounding the sensitivity of polynomial threshold functions":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "degree d chow parameters robustly determine degree d ptfs and algorithmic applications")
  Member "the intersection of two halfspaces has high threshold degree":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "near optimal lower bounds on the threshold degree and sign rank of ac 0")
  Member "pseudorandom generators for polynomial threshold functions":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "degree d chow parameters robustly determine degree d ptfs and algorithmic applications")

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)