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 "computing the independence polynomial in shearer s region for the lll"):
  Abstract: The independence polynomial has been widely studied in algebraic graph theory, in statistical physics, and in algorithms for counting and sampling problems. Seminal results of Weitz (2006) and Sly (2010) have shown the that the computational complexity of approximating the independence polynomial with positive activities is tightly linked to a uniqueness phase transition for a Gibbs measure. #R##N#We study algorithms for approximating the independence polynomial with negative and complex arguments. The independence polynomial with complex arguments may not have a counting interpretation, but it does have strong connections to combinatorics and to statistical physics. The independence polynomial with negative arguments determines the maximal region of probabilities to which the Lov\'{a}sz Local Lemma (LLL) can be extended, and also gives a lower bound on the probability in the LLL's conclusion (Shearer 1985). In statistical physics, complex (and negative) zeros of the independence polynomial relate to existence of phase transitions (Penrose 1963). #R##N#Whereas many algorithms for computing combinatorial polynomials are restricted to the univariate setting, we consider the multivariate independence polynomial, since there is a natural multivariate region of interest -- Shearer's region for the LLL. Our main result is: for any $n$-vertex graph of degree at most $d$, any $\alpha \in (0,1]$, and any complex vector $p$ such that $(1+\alpha) \cdot p$ lies in Shearer's region, there is a deterministic algorithm to approximate the independence polynomial at $p$ within $(1+\epsilon)$ multiplicative error and with runtime $(\frac{n}{\epsilon \alpha})^{O(\log(d)/\alpha)}$. Our results also extend to graphs of unbounded degree that have a bounded connective constant. #R##N#We also give hardness results addressing the dependence of the runtime of the algorithm on the above parameters.

Includes members:
  Member "inapproximability of the independent set polynomial below the shearer threshold":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "the complexity of approximating the matching polynomial in the complex plane")
  Member "convergence of mcmc and loopy bp in the tree uniqueness region for the hard core model":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "spectral independence in high dimensional expanders and applications to the hardcore model")
  Member "fptas for bis with degree bounds on one side":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "counting independent sets and colorings on random regular bipartite graphs")
  Member "an algorithmic proof of the lovasz local lemma via resampling oracles":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "extensions of the algorithmic lovasz local lemma")
  Member "spatial mixing and the connective constant optimal bounds":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "spectral independence in high dimensional expanders and applications to the hardcore model")
  Member "fptas for counting monotone cnf":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "approximate counting the lovasz local lemma and inference in graphical models")
  Member "spatial mixing and approximation algorithms for graphs with bounded connective constant":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "spectral independence in high dimensional expanders and applications to the hardcore model")
  Member "inapproximability for antiferromagnetic spin systems in the tree non uniqueness region":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "spectral approximate inference")

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.DS(Data Structures and Algorithms)