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: "testing low complexity affine invariant properties"
  Abstract: Invariance with respect to linear or affine transformations of the domain is arguably the most common symmetry exhibited by natural algebraic properties. In this work, we show that any low complexity affine-invariant property of multivariate functions over finite fields is testable with a constant number of queries. This immediately reproves, for instance, that the Reed-Muller code over F_p of degree d < p is testable, with an argument that uses no detailed algebraic information about polynomials except that low degree is preserved by composition with affine maps. #R##N#The complexity of an affine-invariant property P refers to the maximum complexity, as defined by Green and Tao (Ann. Math. 2008), of the sets of linear forms used to characterize P. A more precise statement of our main result is that for any fixed prime p >=2 and fixed integer R >= 2, any affine-invariant property P of functions f: F_p^n -> [R] is testable, assuming the complexity of the property is less than p. Our proof involves developing analogs of graph-theoretic techniques in an algebraic setting, using tools from higher-order Fourier analysis.

Connected through hyperedge HE-1 (induced by source paper "testing noisy linear functions for sparsity"):
  with members:
    - "almost optimal distribution free junta testing"
    - "estimating learnability in the sublinear data regime"
    - "tolerant junta testing and the connection to submodular optimization and function isomorphism"
    - "lower bounds for sparse recovery"
    - "a unified framework for testing linear invariant properties"

Connected through hyperedge HE-2 (induced by source paper "using higher order fourier analysis over general fields"):
  with members:
    - "a characterization of locally testable affine invariant properties via decomposition theorems"
    - "estimating the distance from testable affine invariant properties"
    - "algorithmic regularity for polynomials and applications"
    - "every locally characterized affine invariant property is testable"
    - "a unified framework for testing linear invariant properties"
    - "succinct representation of codes with applications to testing"

Connected through hyperedge HE-3 (induced by source paper "testing properties of functions on finite groups"):
  with members:
    - "a characterization of locally testable affine invariant properties via decomposition theorems"
    - "estimating the distance from testable affine invariant properties"
    - "every locally characterized affine invariant property is testable"
    - "partially symmetric functions are efficiently isomorphism testable"

Connected through hyperedge HE-4 (induced by source paper "gowers norm function limits and parameter estimation"):
  with members:
    - "bias vs structure of polynomials in large fields and applications in effective algebraic geometry and coding theory"
    - "using higher order fourier analysis over general fields"
    - "a characterization of locally testable affine invariant properties via decomposition theorems"
    - "list decoding reed muller codes over small fields"
    - "estimating the distance from testable affine invariant properties"
    - "every locally characterized affine invariant property is testable"
    - "a unified framework for testing linear invariant properties"

Connected through hyperedge HE-5 (induced by source paper "a characterization of locally testable affine invariant properties via decomposition theorems"):
  with members:
    - "estimating the distance from testable affine invariant properties"
    - "every locally characterized affine invariant property is testable"
    - "partially symmetric functions are efficiently isomorphism testable"
    - "a unified framework for testing linear invariant properties"

Connected through hyperedge HE-6 (induced by source paper "estimating the distance from testable affine invariant properties"):
  with members:
    - "every locally characterized affine invariant property is testable"
    - "a unified framework for testing linear invariant properties"

Connected through hyperedge HE-7 (induced by source paper "every locally characterized affine invariant property is testable"):
  with members:
    - "a unified framework for testing linear invariant properties"

Connected through hyperedge HE-8 (induced by source paper "a unified framework for testing linear invariant properties"):
  with members:
    - "every locally characterized affine invariant property is testable"
    - "partially symmetric functions are efficiently isomorphism testable"
    - "separations of matroid freeness properties"
    - "succinct representation of codes with applications to testing"
    - "adaptive simulated annealing a near optimal connection between sampling and counting"

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)