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: "pseudorandomness via the discrete fourier transform"
  Abstract: We present a new approach to constructing unconditional pseudorandom generators against classes of functions that involve computing a linear function of the inputs. We give an explicit construction of a pseudorandom generator that fools the discrete Fourier transforms of linear functions with seed-length that is nearly logarithmic (up to polyloglog factors) in the input size and the desired error parameter. Our result gives a single pseudorandom generator that fools several important classes of tests computable in logspace that have been considered in the literature, including halfspaces (over general domains), modular tests and combinatorial shapes. For all these classes, our generator is the first that achieves near logarithmic seed-length in both the input length and the error parameter. Getting such a seed-length is a natural challenge in its own right, which needs to be overcome in order to derandomize RL - a central question in complexity theory. #R##N#Our construction combines ideas from a large body of prior work, ranging from a classical construction of [NN93] to the recent gradually increasing independence paradigm of [KMN11, CRSW13, GMRTV12], while also introducing some novel analytic machinery which might find other applications.

Connected through hyperedge HE-1 (induced by source paper "fourier bounds and pseudorandom generators for product tests"):
  with members:
    - "pseudorandom generators for width 3 branching programs"
    - "pseudorandom generators for read once branching programs in any order"
    - "the coin problem in constant depth sample complexity and parity gates"
    - "analysis of boolean functions"
    - "pseudorandomness and fourier growth bounds for width 3 branching programs"
    - "pseudorandomness for regular branching programs via fourier analysis"
    - "an entropic proof of chang s inequality"
    - "better pseudorandom generators from milder pseudorandom restrictions"

Connected through hyperedge HE-2 (induced by source paper "fast hashing with strong concentration bounds"):
  with members:
    - "optimal streaming and tracking distinct elements with high probability"
    - "faster 64 bit universal hashing using carry less multiplications"
    - "high speed hashing for integers and strings"
    - "from independence to expansion and back again"
    - "generating k independent variables in constant time"
    - "hashing for statistics over k partitions"
    - "bottom k and priority sampling set similarity and subset sums with minimal independence"
    - "simple tabulation fast expanders double tabulation and high independence"

Connected through hyperedge HE-3 (induced by source paper "degree d chow parameters robustly determine degree d ptfs and algorithmic applications"):
  with members:
    - "learning geometric concepts with nasty noise"
    - "hardness of learning noisy halfspaces using polynomial thresholds"
    - "robust estimators in high dimensions without the computational intractability"
    - "complexity theoretic limitations on learning halfspaces"
    - "super linear gate and super quadratic wire lower bounds for depth two and depth three threshold circuits"
    - "a ptas for agnostically learning halfspaces"
    - "analysis of boolean functions"
    - "deterministic approximate counting for juntas of degree 2 polynomial threshold functions"

Connected through hyperedge HE-4 (induced by source paper "fooling polytopes"):
  with members:
    - "fooling intersections of low weight halfspaces"
    - "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"
    - "k independent gaussians fool polynomial threshold functions"

Connected through hyperedge HE-5 (induced by source paper "perfect l_p sampling in a data stream"):
  with members:
    - "optimal random sampling from distributed streams revisited"
    - "optimal lower bounds for universal relation and for samplers and finding duplicates in streams"
    - "heavy hitters via cluster preserving clustering"
    - "beating countsketch for heavy hitters in insertion streams"
    - "stream sampling for frequency cap statistics"
    - "improved concentration bounds for count sketch"
    - "structure aware sampling flexible and accurate summarization"
    - "tight bounds for lp samplers finding duplicates in streams and related problems"

Connected through hyperedge HE-6 (induced by source paper "pseudorandom generators for width 3 branching programs"):
  with members:
    - "pseudorandom generators for read once branching programs in any order"
    - "pseudorandomness and fourier growth bounds for width 3 branching programs"
    - "pseudorandomness for regular branching programs via fourier analysis"
    - "better pseudorandom generators from milder pseudorandom restrictions"

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"
    - "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"
    - "fooling functions of halfspaces under product distributions"

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"
    - "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"
    - "a satisfiability algorithm for sparse depth two threshold circuits"

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)