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: "a unified framework for testing linear invariant properties"
  Abstract: The study of the interplay between the testability of properties of Boolean functions and the invariances acting on their domain which preserve the property was initiated by Kaufman and Sudan (STOC 2008). Invariance with respect to F_2-linear transformations is arguably the most common symmetry exhibited by natural properties of Boolean functions on the hypercube. Hence, an important goal in Property Testing is to describe necessary and sufficient conditions for the testability of linear-invariant properties. This direction was explicitly proposed for investigation in a recent survey of Sudan. #R##N#We obtain the following results: #R##N#1. We show that every linear-invariant property that can be characterized by forbidding induced solutions to a (possibly infinite) set of linear equations can be tested with one-sided error. #R##N#2. We show that every linear-invariant property that can be tested with one-sided error can be characterized by forbidding induced solutions to a (possibly infinite) set of systems of linear equations. #R##N#We conjecture that our result from item (1) can be extended to cover systems of linear equations. We further show that the validity of this conjecture would have the following implications: #R##N#1. It would imply that every linear-invariant property that is closed under restrictions to linear subspaces is testable with one-sided error. Such a result would unify several previous results on testing Boolean functions, such as the testability of low-degree polynomials and of Fourier dimensionality. #R##N#2. It would imply that a linear-invariant property P is testable with one-sided error if and only if P is closed under restrictions to linear subspaces, thus resolving Sudan's problem.

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"
    - "testing low complexity affine invariant properties"
    - "lower bounds for sparse recovery"

Connected through hyperedge HE-2 (induced by source paper "a characterization of constant sample testable properties"):
  with members:
    - "on active and passive testing"
    - "constant time testing and learning of image properties"
    - "trading query complexity for sample based testing and multi testing scalability"
    - "a characterization of locally testable affine invariant properties via decomposition theorems"
    - "new algorithms and lower bounds for monotonicity testing"
    - "active property testing"
    - "partially symmetric functions are efficiently isomorphism testable"

Connected through hyperedge HE-3 (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"
    - "testing low complexity affine invariant properties"
    - "succinct representation of codes with applications to testing"

Connected through hyperedge HE-4 (induced by source paper "trading query complexity for sample based testing and multi testing scalability"):
  with members:
    - "testing formula satisfaction"

Connected through hyperedge HE-5 (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"
    - "testing low complexity affine invariant properties"

Connected through hyperedge HE-6 (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"
    - "testing low complexity affine invariant properties"
    - "partially symmetric functions are efficiently isomorphism testable"

Connected through hyperedge HE-7 (induced by source paper "sunflowers and testing triangle freeness of functions"):
  with members:
    - "on active and passive testing"
    - "improved lower bounds for testing triangle freeness in boolean functions via fast matrix multiplication"

Connected through hyperedge HE-8 (induced by source paper "estimating the distance from testable affine invariant properties"):
  with members:
    - "every locally characterized affine invariant property is testable"
    - "testing low complexity affine invariant properties"

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.DS(Data Structures and Algorithms)