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: "the pattern matrix method journal version"
  Abstract: We develop a novel and powerful technique for communication lower bounds, the pattern matrix method. Specifically, fix an arbitrary function f:{0,1}^n->{0,1} and let A_f be the matrix whose columns are each an application of f to some subset of the variables x_1,x_2,...,x_{4n}. We prove that A_f has bounded-error communication complexity Omega(d), where d is the approximate degree of f. This result remains valid in the quantum model, regardless of prior entanglement. In particular, it gives a new and simple proof of Razborov's breakthrough quantum lower bounds for disjointness and other symmetric predicates. We further characterize the discrepancy, approximate rank, and approximate trace norm of A_f in terms of well-studied analytic properties of f, broadly generalizing several recent results on small-bias communication and agnostic learning. The method of this paper has recently enabled important progress in multiparty communication complexity.

Connected through hyperedge HE-1 (induced by source paper "improved bounds on fourier entropy and min entropy"):
  with members:
    - "on the fourier entropy influence conjecture for extremal classes"
    - "improved lower bounds for the fourier entropy influence conjecture via lexicographic functions"
    - "nearly optimal separations between communication or query complexity and partitions"
    - "low sensitivity functions from unambiguous certificates"
    - "degree and sensitivity tails of two distributions"
    - "polynomial bounds for decoupling with applications"
    - "almost quadratic gap between partition complexity and query communication complexity"
    - "analysis of boolean functions"

Connected through hyperedge HE-2 (induced by source paper "bounding the sensitivity of polynomial threshold functions"):
  with members:
    - "average sensitivity and noise sensitivity of polynomial threshold functions"
    - "bounded independence fools halfspaces"
    - "a regularity lemma and low weight approximators for low degree polynomial threshold functions"
    - "pseudorandom generators for polynomial threshold functions"

Connected through hyperedge HE-3 (induced by source paper "hardness amplification in proof complexity"):
  with members:
    - "multiparty communication complexity of disjointness"
    - "disjointness is hard in the multi party number on the forehead model"

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)