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: "on the structure of boolean functions with small spectral norm"
  Abstract: In this paper we prove results regarding Boolean functions with small spectral norm (the spectral norm of f is $\|\hat{f}\|_1=\sum_{\alpha}|\hat{f}(\alpha)|$). Specifically, we prove the following results for functions $f:\{0,1\}^n \to \{0,1\}$ with $\|\hat{f}\|_1=A$. #R##N#1. There is a subspace $V$ of co-dimension at most $A^2$ such that $f|_V$ is constant. #R##N#2. f can be computed by a parity decision tree of size $2^{A^2}n^{2A}$. (a parity decision tree is a decision tree whose nodes are labeled with arbitrary linear functions.) #R##N#3. If in addition f has at most s nonzero Fourier coefficients, then f can be computed by a parity decision tree of depth $A^2 \log s$. #R##N#4. For every $0<\epsilon$ there is a parity decision tree of depth $O(A^2 + \log(1/\epsilon))$ and size $2^{O(A^2)} \cdot \min\{1/\epsilon^2,O(\log(1/\epsilon))^{2A}\}$ that \epsilon-approximates f. Furthermore, this tree can be learned, with probability $1-\delta$, using $\poly(n,\exp(A^2),1/\epsilon,\log(1/\delta))$ membership queries. #R##N#All the results above also hold (with a slight change in parameters) to functions $f:Z_p^n\to \{0,1\}$.

Connected through hyperedge HE-1 (induced by source paper "fast fourier sparsity testing"):
  with members:
    - "robust estimators in high dimensions without the computational intractability"
    - "analysis of boolean functions"
    - "estimating the distance from testable affine invariant properties"
    - "fourier sparsity spectral norm and the log rank conjecture"
    - "nearly optimal sparse fourier transform"
    - "on the parity complexity measures of boolean functions"
    - "on the communication complexity of xor functions"

Connected through hyperedge HE-2 (induced by source paper "linear sketching over mathbb f_2"):
  with members:
    - "an inequality for the fourier spectrum of parity decision trees"
    - "analysis of boolean functions"
    - "a composition theorem for parity kill number"
    - "improved bounds for the randomized decision tree complexity of recursive majority"
    - "on the parity complexity measures of boolean functions"
    - "on the communication complexity of xor functions"

Connected through hyperedge HE-3 (induced by source paper "learning boolean functions with concentrated spectra"):
  with members:
    - "delving deep into rectifiers surpassing human level performance on imagenet classification"
    - "the loss surfaces of multilayer networks"
    - "deep speech scaling up end to end speech recognition"
    - "deep scattering spectrum"
    - "living on the edge phase transitions in convex programs with random data"
    - "robust 1 bit compressive sensing via binary stable embeddings of sparse vectors"
    - "theoretical and empirical results for recovery from multiple measurements"

Connected through hyperedge HE-4 (induced by source paper "an inequality for the fourier spectrum of parity decision trees"):
  with members:
    - "a composition theorem for parity kill number"
    - "improved bounds for the randomized decision tree complexity of recursive majority"
    - "open problems in analysis of boolean functions"
    - "on the parity complexity measures of boolean functions"

Connected through hyperedge HE-5 (induced by source paper "fourier sparsity of gf 2 polynomials"):
  with members:
    - "communication is bounded by root of rank"
    - "spectral norm of symmetric functions"
    - "on the communication complexity of xor functions"

Connected through hyperedge HE-6 (induced by source paper "pseudorandomness and fourier growth bounds for width 3 branching programs"):
  with members:
    - "fourier sparsity spectral norm and the log rank conjecture"
    - "pseudorandomness for regular branching programs via fourier analysis"
    - "spectral norm of symmetric functions"
    - "better pseudorandom generators from milder pseudorandom restrictions"

Connected through hyperedge HE-7 (induced by source paper "sub linear upper bounds on fourier dimension of boolean functions in terms of fourier sparsity"):
  with members:
    - "analysis of boolean functions"
    - "fourier sparsity spectral norm and the log rank conjecture"

Connected through hyperedge HE-8 (induced by source paper "a composition theorem for parity kill number"):
  with members:
    - "analysis of boolean functions"
    - "two structural results for low degree polynomials and applications"
    - "communication is bounded by root of rank"
    - "on the parity complexity measures of boolean functions"
    - "variations on the sensitivity conjecture"
    - "on the communication complexity of xor functions"
    - "every decision tree has an influential variable"

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)