human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "deterministic approximate counting for degree 2 polynomial threshold functions"):
  Abstract: We give a {\em deterministic} algorithm for approximately computing the fraction of Boolean assignments that satisfy a degree-$2$ polynomial threshold function. Given a degree-2 input polynomial $p(x_1,\dots,x_n)$ and a parameter $\eps > 0$, the algorithm approximates \[ \Pr_{x \sim \{-1,1\}^n}[p(x) \geq 0] \] to within an additive $\pm \eps$ in time $\poly(n,2^{\poly(1/\eps)})$. Note that it is NP-hard to determine whether the above probability is nonzero, so any sort of multiplicative approximation is almost certainly impossible even for efficient randomized algorithms. This is the first deterministic algorithm for this counting problem in which the running time is polynomial in $n$ for $\eps= o(1)$. For "regular" polynomials $p$ (those in which no individual variable's influence is large compared to the sum of all $n$ variable influences) our algorithm runs in $\poly(n,1/\eps)$ time. The algorithm also runs in $\poly(n,1/\eps)$ time to approximate $\Pr_{x \sim N(0,1)^n}[p(x) \geq 0]$ to within an additive $\pm \eps$, for any degree-2 polynomial $p$. #R##N#As an application of our counting result, we give a deterministic FPT multiplicative $(1 \pm \eps)$-approximation algorithm to approximate the $k$-th absolute moment $\E_{x \sim \{-1,1\}^n}[|p(x)^k|]$ of a degree-2 polynomial. The algorithm's running time is of the form $\poly(n) \cdot f(k,1/\eps)$.

Includes members:
  Member "deterministic approximate counting for juntas of degree 2 polynomial threshold functions":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "degree d chow parameters robustly determine degree d ptfs and algorithmic applications")
  Member "efficient deterministic approximate counting for low degree polynomial threshold functions":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "deterministic search for cnf satisfying assignments in almost polynomial time")
  Member "a pseudorandom generator for polynomial threshold functions of gaussian with subpolynomial seed length":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "fooling polytopes")
  Member "the inverse shapley value problem":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "degree d chow parameters robustly determine degree d ptfs and algorithmic applications")
  Member "nearly optimal solutions for the chow parameters problem and low weight approximation of halfspaces":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "nearly tight bounds for robust proper learning of halfspaces with a margin")
  Member "correlation decay up to uniqueness in spin systems":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "spectral independence in high dimensional expanders and applications to the hardcore model")
  Member "a small prg for polynomial threshold functions of gaussians":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "fooling polytopes")
  Member "hardness results for agnostically learning low degree polynomial threshold functions":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "nearly tight bounds for robust proper learning of halfspaces with a margin")

Question: Please tell me which class the source paper 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)