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: "polynomial threshold functions structure approximation and pseudorandomness"
  Abstract: We study the computational power of polynomial threshold functions, that is, threshold functions of real polynomials over the boolean cube. We provide two new results bounding the computational power of this model. #R##N#Our first result shows that low-degree polynomial threshold functions cannot approximate any function with many influential variables. We provide a couple of examples where this technique yields tight approximation bounds. #R##N#Our second result relates to constructing pseudorandom generators fooling low-degree polynomial threshold functions. This problem has received attention recently, where Diakonikolas et al proved that $k$-wise independence suffices to fool linear threshold functions. We prove that any low-degree polynomial threshold function, which can be represented as a function of a small number of linear threshold functions, can also be fooled by $k$-wise independence. We view this as an important step towards fooling general polynomial threshold functions, and we discuss a plausible approach achieving this goal based on our techniques. #R##N#Our results combine tools from real approximation theory, hyper-contractive inequalities and probabilistic methods. In particular, we develop several new tools in approximation theory which may be of independent interest.

Connected through hyperedge HE-1 (induced by source paper "a ptas for agnostically learning halfspaces"):
  with members:
    - "complexity theoretic limitations on learning halfspaces"
    - "complexity theoretic limitations on learning dnf s"
    - "the power of localization for efficiently learning linear separators with noise"
    - "from average case complexity to improper learning complexity"
    - "the complexity of learning halfspaces using generalized linear methods"
    - "minimizing the misclassification error rate using a surrogate convex loss"
    - "bounded independence fools halfspaces"
    - "bounded independence fools degree 2 threshold functions"

Connected through hyperedge HE-2 (induced by source paper "almost optimal pseudorandom generators for spherical caps"):
  with members:
    - "a pseudorandom generator for polynomial threshold functions of gaussian with subpolynomial seed length"
    - "a method of moments for mixture models and hidden markov models"
    - "a small prg for polynomial threshold functions of gaussians"
    - "k independent gaussians fool polynomial threshold functions"
    - "bounded independence fools halfspaces"
    - "bounded independence fools degree 2 threshold functions"

Connected through hyperedge HE-3 (induced by source paper "deterministic approximate counting for juntas of degree 2 polynomial threshold functions"):
  with members:
    - "deterministic approximate counting for degree 2 polynomial threshold functions"
    - "the inverse shapley value problem"
    - "nearly optimal solutions for the chow parameters problem and low weight approximation of halfspaces"
    - "fooling functions of halfspaces under product distributions"
    - "hardness results for agnostically learning low degree polynomial threshold functions"
    - "k independent gaussians fool polynomial threshold functions"
    - "bounded independence fools halfspaces"
    - "bounding the sensitivity of polynomial threshold functions"

Connected through hyperedge HE-4 (induced by source paper "fooling functions of halfspaces under product distributions"):
  with members:
    - "an invariance principle for polytopes"
    - "agnostic learning of monomials by halfspaces is hard"
    - "bounded independence fools halfspaces"
    - "pseudorandom generators for polynomial threshold functions"
    - "bounded independence fools degree 2 threshold functions"

Connected through hyperedge HE-5 (induced by source paper "a regularity lemma and low weight approximators for low degree polynomial threshold functions"):
  with members:
    - "k independent gaussians fool polynomial threshold functions"
    - "average sensitivity and noise sensitivity of polynomial threshold functions"
    - "improved approximation of linear threshold functions"
    - "bounded independence fools halfspaces"
    - "bounding the sensitivity of polynomial threshold functions"
    - "the intersection of two halfspaces has high threshold degree"
    - "pseudorandom generators for polynomial threshold functions"
    - "bounded independence fools degree 2 threshold functions"

Connected through hyperedge HE-6 (induced by source paper "pseudorandom generators for polynomial threshold functions"):
  with members:
    - "an invariance principle for polytopes"
    - "fooling functions of halfspaces under product distributions"
    - "polynomial time approximation schemes for knapsack and related counting problems using branching programs"
    - "bounded independence fools halfspaces"
    - "bounding the sensitivity of polynomial threshold functions"
    - "a regularity lemma and low weight approximators for low degree polynomial threshold functions"

Connected through hyperedge HE-7 (induced by source paper "bounded independence fools degree 2 threshold functions"):
  with members:
    - "an invariance principle for polytopes"
    - "fooling functions of halfspaces under product distributions"
    - "bounded independence fools halfspaces"
    - "the intersection of two halfspaces has high threshold degree"
    - "a regularity lemma and low weight approximators for low degree polynomial threshold functions"
    - "pseudorandom generators for polynomial threshold functions"

Connected through hyperedge HE-8 (induced by source paper "bounded independence fools halfspaces"):
  with members:
    - "fooling functions of halfspaces under product distributions"
    - "improved approximation of linear threshold functions"
    - "bounding the sensitivity of polynomial threshold functions"
    - "a regularity lemma and low weight approximators for low degree polynomial threshold functions"
    - "bounded independence fools degree 2 threshold functions"

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.CC(Computational Complexity)