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 regularity lemma and low weight approximators for low degree polynomial threshold functions"
  Abstract: We give a "regularity lemma" for degree-d polynomial threshold functions (PTFs) over the Boolean cube {-1,1}^n. This result shows that every degree-d PTF can be decomposed into a constant number of subfunctions such that almost all of the subfunctions are close to being regular PTFs. Here a "regular PTF is a PTF sign(p(x)) where the influence of each variable on the polynomial p(x) is a small fraction of the total influence of p. #R##N#As an application of this regularity lemma, we prove that for any constants d \geq 1, \eps \geq 0, every degree-d PTF over n variables has can be approximated to accuracy eps by a constant-degree PTF that has integer weights of total magnitude O(n^d). This weight bound is shown to be optimal up to constant factors.

Connected through hyperedge HE-1 (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"
    - "pseudorandomness via the discrete fourier transform"
    - "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"

Connected through hyperedge HE-2 (induced by source paper "fooling intersections of low weight halfspaces"):
  with members:
    - "average case lower bounds and satisfiability algorithms for small threshold circuits"
    - "pseudorandomness via the discrete fourier transform"
    - "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"

Connected through hyperedge HE-3 (induced by source paper "non interactive simulation of correlated distributions is decidable"):
  with members:
    - "decidability of non interactive simulation of joint distributions"
    - "on non interactive simulation of joint distributions"
    - "lower bounds on the size of semidefinite programming relaxations"
    - "deterministic approximate counting for juntas of degree 2 polynomial threshold functions"
    - "efficient deterministic approximate counting for low degree polynomial threshold functions"

Connected through hyperedge HE-4 (induced by source paper "decidability of non interactive simulation of joint distributions"):
  with members:
    - "on the role of shared randomness in simultaneous communication"
    - "information complexity is computable"
    - "on the duality of additivity and tensorization"
    - "on non interactive simulation of joint distributions"
    - "communication complexity of permutation invariant functions"
    - "communication with imperfectly shared randomness"
    - "information equals amortized communication"
    - "reductions between expansion problems"

Connected through hyperedge HE-5 (induced by source paper "a noisy influence regularity lemma for boolean functions"):
  with members:
    - "analysis of boolean functions"

Connected through hyperedge HE-6 (induced by source paper "weighted polynomial approximations limits for learning and pseudorandomness"):
  with members:
    - "pseudorandomness for concentration bounds and signed majorities"
    - "analysis of boolean functions"
    - "agnostic learning of disjunctions on symmetric distributions"
    - "approximate resilience monotonicity and the complexity of agnostic learning"
    - "pseudorandomness for regular branching programs via fourier analysis"
    - "the complexity of learning halfspaces using generalized linear methods"
    - "fooling functions of halfspaces under product distributions"
    - "a derandomized sparse johnson lindenstrauss transform"

Connected through hyperedge HE-7 (induced by source paper "heat and noise on cubes and spheres the sensitivity of randomly rotated polynomial threshold functions"):
  with members:
    - "analysis of boolean functions"
    - "bounding the sensitivity of polynomial threshold functions"

Connected through hyperedge HE-8 (induced by source paper "deterministic approximate counting for degree 2 polynomial threshold functions"):
  with members:
    - "deterministic approximate counting for juntas of degree 2 polynomial threshold functions"
    - "efficient deterministic approximate counting for low degree polynomial threshold functions"
    - "a pseudorandom generator for polynomial threshold functions of gaussian with subpolynomial seed length"
    - "the inverse shapley value problem"
    - "nearly optimal solutions for the chow parameters problem and low weight approximation of halfspaces"
    - "correlation decay up to uniqueness in spin systems"
    - "a small prg for polynomial threshold functions of gaussians"
    - "hardness results for agnostically learning low degree polynomial threshold functions"

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)