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: "new constructive aspects of the lovasz local lemma"
  Abstract: The Lov\'{a}sz Local Lemma (LLL) states that the probability that none of a set of "bad" events happens is nonzero if the probability of each event is small compared to the number of bad events it depends on. A series of results have provided algorithms to efficiently construct structures whose existence is (non-constructively) guaranteed by the full asymmetric LLL, culminating in the recent breakthrough of Moser & Tardos. We show that the output distribution of the Moser-Tardos procedure has sufficient randomness, leading to two classes of algorithmic applications. We first show that when an LLL application provides a small amount of slack, the running time of the Moser-Tardos algorithm is polynomial in the number of underlying independent variables (not events!), and can thus be used to give efficient constructions in cases where the underlying proof applies the LLL to super-polynomially many events (or where finding a bad event that holds is computationally hard). We demonstrate our method on applications including: the first constant-factor approximation algorithm for the Santa Claus problem, as well as efficient algorithms for acyclic edge coloring, non-repetitive graph colorings, and Ramsey-type graphs. Second, we show applications to cases where a few of the bad events can hold, leading to the first such algorithmic applications of the LLL: MAX $k$-SAT is an illustrative example of this.

Connected through hyperedge HE-1 (induced by source paper "fast sampling and counting k sat solutions in the local lemma regime"):
  with members:
    - "algorithms for bis hard problems on expander graphs"
    - "algorithmic pirogov sinai theory"
    - "counting hypergraph colorings in the local lemma regime"
    - "convergence of mcmc and loopy bp in the tree uniqueness region for the hard core model"
    - "a faster approximation algorithm for the gibbs partition function"
    - "approximate counting the lovasz local lemma and inference in graphical models"
    - "parallel algorithms and concentration bounds for the lovasz local lemma via witness dags"
    - "approximation via correlation decay when strong spatial mixing fails"

Connected through hyperedge HE-2 (induced by source paper "counting solutions to random cnf formulas"):
  with members:
    - "counting independent sets and colorings on random regular bipartite graphs"
    - "counting hypergraph colorings in the local lemma regime"
    - "sampling random colorings of sparse random graphs"
    - "approximate counting the lovasz local lemma and inference in graphical models"
    - "approximation via correlation decay when strong spatial mixing fails"
    - "on the concentration of the number of solutions of random satisfiability formulas"
    - "deterministic algorithms for the lovasz local lemma"
    - "a constructive proof of the general lovasz local lemma"

Connected through hyperedge HE-3 (induced by source paper "deterministic algorithms for the lovasz local lemma simpler more general and more parallel"):
  with members:
    - "algorithms for weighted independent transversals and strong colouring"
    - "deterministic parallel algorithms for bilinear objective functions"
    - "sublogarithmic distributed algorithms for lov asz local lemma and the complexity hierarchy"
    - "lopsidependency in the moser tardos framework beyond the lopsided lovasz local lemma"
    - "deterministic parallel algorithms for fooling polylogarithmic juntas and the lovasz local lemma"
    - "algorithmic and enumerative aspects of the moser tardos distribution"
    - "parallel algorithms and concentration bounds for the lovasz local lemma via witness dags"
    - "deterministic algorithms for the lovasz local lemma"

Connected through hyperedge HE-4 (induced by source paper "new notions and constructions of sparsification for graphs and hypergraphs"):
  with members:
    - "spectral sparsification of hypergraphs"
    - "finding a bounded degree expander inside a dense one"
    - "spectral sparsification and regret minimization beyond matrix multiplicative updates"
    - "sketching cuts in graphs and hypergraphs"
    - "an efficient algorithm for unweighted spectral graph sparsification"
    - "twice ramanujan sparsifiers"
    - "graph sparsification by effective resistances"
    - "nearly linear time algorithms for graph partitioning graph sparsification and solving linear systems"

Connected through hyperedge HE-5 (induced by source paper "restricted max min allocation approximation and integrality gap"):
  with members:
    - "integrality gap of the configuration lp for the restricted max min fair allocation"
    - "a tale of santa claus hypergraphs and matroids"
    - "restricted max min fair allocation"
    - "combinatorial algorithm for restricted max min fair allocation"
    - "quasi polynomial local search for restricted max min fair allocation"
    - "a new approximation technique for resource allocation problems"
    - "on allocating goods to maximize fairness"

Connected through hyperedge HE-6 (induced by source paper "algorithms for weighted independent transversals and strong colouring"):
  with members:
    - "lopsidependency in the moser tardos framework beyond the lopsided lovasz local lemma"
    - "algorithmic and enumerative aspects of the moser tardos distribution"
    - "finding perfect matchings in bipartite hypergraphs"
    - "deterministic algorithms for the lovasz local lemma"
    - "a constructive proof of the general lovasz local lemma"

Connected through hyperedge HE-7 (induced by source paper "dynamic sampling from graphical models"):
  with members:
    - "distributed symmetry breaking in sampling optimal distributed randomly coloring with fewer colors"
    - "a simple parallel and distributed sampling technique local glauber dynamics"
    - "tight bounds for popping algorithms"
    - "sublogarithmic distributed algorithms for lov asz local lemma and the complexity hierarchy"
    - "what can be sampled locally"
    - "a polynomial time approximation algorithm for all terminal network reliability"
    - "uniform sampling through the lov asz local lemma"
    - "convergence of mcmc and loopy bp in the tree uniqueness region for the hard core model"

Connected through hyperedge HE-8 (induced by source paper "beyond the lovasz local lemma point to set correlations and their algorithmic applications"):
  with members:
    - "a local lemma for focused stochastic algorithms"
    - "commutative algorithms approximate the lll distribution"
    - "algorithmic and enumerative aspects of the moser tardos distribution"
    - "commutativity in the algorithmic lovasz local lemma"
    - "parallel algorithms and concentration bounds for the lovasz local lemma via witness dags"
    - "an algorithmic proof of the lovasz local lemma via resampling oracles"
    - "entropy compression method applied to graph colorings"
    - "application of entropy compression in pattern avoidance"

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)