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 "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.

Includes members:
  Member "pseudorandomness for concentration bounds and signed majorities":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "weighted polynomial approximations limits for learning and pseudorandomness")
  Member "almost optimal pseudorandom generators for spherical caps":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "beating the perils of non convexity guaranteed training of neural networks using tensor methods")
  Member "inequalities and tail bounds for elementary symmetric polynomial with applications":
    also connected through other hyperedges:
      (none)
  Member "an invariance principle for polytopes":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "kruskal katona for convex sets with applications")
  Member "a pseudorandom generator for polynomial threshold functions of gaussian with subpolynomial seed length":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "fooling polytopes")
  Member "better pseudorandom generators from milder pseudorandom restrictions":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "exponentially faster shortest paths in the congested clique")
  Member "a small prg for polynomial threshold functions of gaussians":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "fooling polytopes")
  Member "fooling functions of halfspaces under product distributions":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "algorithms and lower bounds for de morgan formulas of low communication leaf gates")

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)