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: "bounded independence fools halfspaces"
  Abstract: We show that any distribution on {-1,1}^n that is k-wise independent fools any halfspace h with error \eps for k = O(\log^2(1/\eps) /\eps^2). Up to logarithmic factors, our result matches a lower bound by Benjamini, Gurel-Gurevich, and Peled (2007) showing that k = \Omega(1/(\eps^2 \cdot \log(1/\eps))). Using standard constructions of k-wise independent distributions, we obtain the first explicit pseudorandom generators G: {-1,1}^s --> {-1,1}^n that fool halfspaces. Specifically, we fool halfspaces with error eps and seed length s = k \log n = O(\log n \cdot \log^2(1/\eps) /\eps^2). #R##N#Our approach combines classical tools from real approximation theory with structural results on halfspaces by Servedio (Computational Complexity 2007).

Connected through hyperedge HE-1 (induced by source paper "list decodable subspace recovery via sum of squares"):
  with members:
    - "list decodable learning via sum of squares"
    - "an overview of robust subspace recovery"
    - "high dimensional robust mean estimation in nearly linear time"
    - "static and dynamic robust pca and matrix completion a review"
    - "better agnostic clustering via relaxed tensor norms"
    - "list decodable robust mean estimation and learning mixtures of spherical gaussians"
    - "agnostic estimation of mean and covariance"
    - "robust estimators in high dimensions without the computational intractability"

Connected through hyperedge HE-2 (induced by source paper "list decodable linear regression"):
  with members:
    - "list decodable learning via sum of squares"
    - "efficient algorithms and lower bounds for robust linear regression"
    - "high dimensional robust mean estimation in nearly linear time"
    - "robustly learning a gaussian getting optimal error efficiently"
    - "polynomial time tensor decompositions with sum of squares"
    - "agnostic estimation of mean and covariance"
    - "robust estimators in high dimensions without the computational intractability"
    - "settling the polynomial learnability of mixtures of gaussians"

Connected through hyperedge HE-3 (induced by source paper "fooling polytopes"):
  with members:
    - "fooling intersections of low weight halfspaces"
    - "pseudorandomness via the discrete fourier transform"
    - "analysis of boolean functions"
    - "the average sensitivity of an intersection of half spaces"
    - "an invariance principle for polytopes"
    - "a pseudorandom generator for polynomial threshold functions of gaussian with subpolynomial seed length"
    - "a small prg for polynomial threshold functions of gaussians"
    - "fooling functions of halfspaces under product distributions"

Connected through hyperedge HE-4 (induced by source paper "average case lower bounds and satisfiability algorithms for small threshold circuits"):
  with members:
    - "analysis of boolean functions"
    - "new algorithms and lower bounds for circuits with linear threshold gates"
    - "a tail bound for read k families of functions"
    - "a satisfiability algorithm for sparse depth two threshold circuits"
    - "a satisfiability algorithm for ac 0"
    - "average sensitivity and noise sensitivity of polynomial threshold functions"
    - "bounding the sensitivity of polynomial threshold functions"
    - "pseudorandom generators for polynomial threshold functions"

Connected through hyperedge HE-5 (induced by source paper "deterministic search for cnf satisfying assignments in almost polynomial time"):
  with members:
    - "on polynomial approximations to ac 0"
    - "pseudorandomness for regular branching programs via fourier analysis"
    - "efficient deterministic approximate counting for low degree polynomial threshold functions"
    - "better pseudorandom generators from milder pseudorandom restrictions"
    - "fooling functions of halfspaces under product distributions"
    - "pseudorandom generators for polynomial threshold functions"
    - "bounded independence fools degree 2 threshold functions"

Connected through hyperedge HE-6 (induced by source paper "a faster fptas for knapsack"):
  with members:
    - "pseudorandom generators for polynomial threshold functions"

Connected through hyperedge HE-7 (induced by source paper "fooling intersections of low weight halfspaces"):
  with members:
    - "average case lower bounds and satisfiability algorithms for small threshold circuits"
    - "pseudorandomness via the discrete fourier transform"
    - "analysis of boolean functions"
    - "the average sensitivity of an intersection of half spaces"
    - "deterministic approximate counting for juntas of degree 2 polynomial threshold functions"
    - "efficient deterministic approximate counting for low degree polynomial threshold functions"
    - "an invariance principle for polytopes"
    - "a robust khintchine inequality and algorithms for computing optimal constants in fourier analysis and high dimensional geometry"

Connected through hyperedge HE-8 (induced by source paper "quantified derandomization of linear threshold circuits"):
  with members:
    - "deterministic search for cnf satisfying assignments in almost polynomial time"
    - "average case lower bounds and satisfiability algorithms for small threshold circuits"
    - "randomness extraction in ac0 and with small locality"
    - "pseudorandomness via the discrete fourier transform"
    - "super linear gate and super quadratic wire lower bounds for depth two and depth three threshold circuits"
    - "analysis of boolean functions"
    - "new algorithms and lower bounds for circuits with linear threshold gates"
    - "almost optimal pseudorandom generators for spherical caps"

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)